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Journal articles on the topic 'Adaptive computing systems Signal processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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1

Pfänder, O. A., H. J. Pfleiderer, and S. W. Lachowicz. "Configurable multiplier modules for an adaptive computing system." Advances in Radio Science 4 (September 6, 2006): 231–36. http://dx.doi.org/10.5194/ars-4-231-2006.

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Abstract. The importance of reconfigurable hardware is increasing steadily. For example, the primary approach of using adaptive systems based on programmable gate arrays and configurable routing resources has gone mainstream and high-performance programmable logic devices are rivaling traditional application-specific hardwired integrated circuits. Also, the idea of moving from the 2-D domain into a 3-D design which stacks several active layers above each other is gaining momentum in research and industry, to cope with the demand for smaller devices with a higher scale of integration. However, optimized arithmetic blocks in course-grain reconfigurable arrays as well as field-programmable architectures still play an important role. In countless digital systems and signal processing applications, the multiplication is one of the critical challenges, where in many cases a trade-off between area usage and data throughput has to be made. But the a priori choice of word-length and number representation can also be replaced by a dynamic choice at run-time, in order to improve flexibility, area efficiency and the level of parallelism in computation. In this contribution, we look at an adaptive computing system called 3-D-SoftChip to point out what parameters are crucial to implement flexible multiplier blocks into optimized elements for accelerated processing. The 3-D-SoftChip architecture uses a novel approach to 3-dimensional integration based on flip-chip bonding with indium bumps. The modular construction, the introduction of interfaces to realize the exchange of intermediate data, and the reconfigurable sign handling approach will be explained, as well as a beneficial way to handle and distribute the numerous required control signals.

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CHO, KILSEOK, ALAN D. GEORGE, RAJ SUBRAMANIYAN, and KEONWOOK KIM. "PARALLEL ALGORITHMS FOR ADAPTIVE MATCHED-FIELD PROCESSING ON DISTRIBUTED ARRAY SYSTEMS." Journal of Computational Acoustics 12, no. 02 (June 2004): 149–74. http://dx.doi.org/10.1142/s0218396x04002274.

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Matched-field processing (MFP) localizes sources more accurately than plane-wave beamforming by employing full-wave acoustic propagation models for the cluttered ocean environment. The minimum variance distortionless response MFP (MVDR–MFP) algorithm incorporates the MVDR technique into the MFP algorithm to enhance beamforming performance. Such an adaptive MFP algorithm involves intensive computational and memory requirements due to its complex acoustic model and environmental adaptation. The real-time implementation of adaptive MFP algorithms for large surveillance areas presents a serious computational challenge where high-performance embedded computing and parallel processing may be required to meet real-time constraints. In this paper, three parallel algorithms based on domain decomposition techniques are presented for the MVDR–MFP algorithm on distributed array systems. The parallel performance factors in terms of execution times, communication times, parallel efficiencies, and memory capacities are examined on three potential distributed systems including two types of digital signal processor arrays and a cluster of personal computers. The performance results demonstrate that these parallel algorithms provide a feasible solution for real-time, scalable, and cost-effective adaptive beamforming on embedded, distributed array systems.

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Garmash, Vitaliy, Yuriy Petrov, Andrey Andreev, and Anatoly Zaitsev. "Adaptive Matching of the Radar Signal and Image Display Device Dynamic Ranges." International Journal of Mathematical, Engineering and Management Sciences 4, no. 6 (December 1, 2019): 1448–58. http://dx.doi.org/10.33889/ijmems.2019.4.6-114.

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This article presents nonlinear radar signal processing method to form an image of the Earth's surface. The method proposes to match the dynamic ranges of the received signal and of the visualization device. The essence of the method is adaptive nonlinear signal processing, which provides better local contrast of radar images and improves discrimination of individual objects. The computational complexity of the proposed algorithm is optimized and allows real-time implementation in the airborne computing systems with limited computational power. Objects with large RCS merged into large illuminated "spots"; their visibility on the surrounding background has been reduced, unwanted effects are due to the fact that the above algorithms have a single point effect. To overcome the problems, the «Retinex» algorithm is usually used. They do not take into account the local neighborhood of pixels; therefore, in cases where the image contains both highly dark and strongly light local areas, these algorithms cannot provide high-quality matching of dynamic ranges.

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Yu, Zhenhao, Fang Liu, Yinquan Yuan, Sihan Li, and Zhengying Li. "Signal Processing for Time Domain Wavelengths of Ultra-Weak FBGs Array in Perimeter Security Monitoring Based on Spark Streaming." Sensors 18, no. 9 (September 4, 2018): 2937. http://dx.doi.org/10.3390/s18092937.

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To detect perimeter intrusion accurately and quickly, a stream computing technology was used to improve real-time data processing in perimeter intrusion detection systems. Based on the traditional density-based spatial clustering of applications with noise (T-DBSCAN) algorithm, which depends on manual adjustments of neighborhood parameters, an adaptive parameters DBSCAN (AP-DBSCAN) method that can achieve unsupervised calculations was proposed. The proposed AP-DBSCAN method was implemented on a Spark Streaming platform to deal with the problems of data stream collection and real-time analysis, as well as judging and identifying the different types of intrusion. A number of sensing and processing experiments were finished and the experimental data indicated that the proposed AP-DBSCAN method on the Spark Streaming platform exhibited a fine calibration capacity for the adaptive parameters and the same accuracy as the T-DBSCAN method without the artificial setting of neighborhood parameters, in addition to achieving good performances in the perimeter intrusion detection systems.

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Chen, Kuan-Ting, Wei-Hsuan Ma, Yin-Tsung Hwang, and Kuan-Ying Chang. "A Low Complexity, High Throughput DoA Estimation Chip Design for Adaptive Beamforming." Electronics 9, no. 4 (April 13, 2020): 641. http://dx.doi.org/10.3390/electronics9040641.

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Direction of Arrival (DoA) estimation is essential to adaptive beamforming widely used in many radar and wireless communication systems. Although many estimation algorithms have been investigated, most of them focus on the performance enhancement aspect but overlook the computing complexity or the hardware implementation issues. In this paper, a low-complexity yet effective DoA estimation algorithm and the corresponding hardware accelerator chip design are presented. The proposed algorithm features a combination of signal sub-space projection and parallel matching pursuit techniques, i.e., applying signal projection first before performing matching pursuit from a codebook. This measure helps minimize the interference from noise sub-space and makes the matching process free of extra orthogonalization computations. The computing complexity can thus be reduced significantly. In addition, estimations of all signal sources can be performed in parallel without going through a successive update process. To facilitate an efficient hardware implementation, the computing scheme of the estimation algorithm is also optimized. The most critical part of the algorithm, i.e., calculating the projection matrix, is largely simplified and neatly accomplished by using QR decomposition. In addition, the proposed scheme supports parallel matches of all signal sources from a beamforming codebook to improve the processing throughput. The algorithm complexity analysis shows that the proposed scheme outperforms other well-known estimation algorithms significantly under various system configurations. The performance simulation results further reveal that, subject to a beamforming codebook with a 5° angular resolution, the Root Mean Square (RMS) error of angle estimations is only 0.76° when Signal to Noise Ratio (SNR) = 20 dB. The estimation accuracy outpaces other matching pursuit based approaches and is close to that of the classic Estimation of Signal Parameters Via Rotational Invariance Techniques (ESPRIT) scheme but requires only one fifth of its computing complexity. In developing the hardware accelerator design, pipelined Coordinate Rotation Digital Computer (CORDIC) processors consisting of simple adders and shifters are employed to implement the basic trigonometric operations needed in QR decomposition. A systolic array architecture is developed as the computing kernel for QR decomposition. Other computing modules are also realized using various linear systolic arrays and chained together seamlessly to maximize the computing throughput. A Taiwan Semiconductor Manufacturing Company (TSMC) 40 nm CMOS process was chosen as the implementation technology. The gate count of the chip design is 454.4k, featuring a core size of 0.76 mm 2 , and can operate up to 333 MHz. This suggests that one DoA estimation, with up to three signal sources, can be performed every 2.38 μs.

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Herment, A., and J. F. Giovannelli. "An Adaptive Approach to Computing the Spectrum and Mean Frequency of Doppler Signals." Ultrasonic Imaging 17, no. 1 (January 1995): 1–26. http://dx.doi.org/10.1177/016173469501700101.

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Modern ultrasound Doppler systems are facing the problem of processing increasingly shorter data sets. Spectral analysis of the strongly nonstationary Doppler signal needs to shorten the analysis window while maintaining a low variance and high resolution spectrum. Color flow imaging requires estimation of the Doppler mean frequency from even shorter Doppler data sets to obtain both a high frame rate and high spatial resolution. We reconsider these two estimation problems in light of adaptive methods. A regularized parametric method for spectral analysis as well as an adapted mean frequency estimator are developed. The choice of the adaptive criterion is then addressed and adaptive spectral and mean frequency estimators are developed to minimize the mean square error on estimation in the presence of noise. Two suboptimal spectral and mean-frequency estimators are then derived for real-time applications. Finally, their performance is compared to that of both the FFT based periodogram and the AR parametric spectral analysis for the spectral estimator, and, to both the correlation angle and the Kristoffersen's [8] estimators for the mean frequency estimator using Doppler data recorded in vitro.

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FATEMIZADEH, EMAD, and PARISA SHOOSHTARI. "ROI-BASED 3D HUMAN BRAIN MAGNETIC RESONANCE IMAGES COMPRESSION USING ADAPTIVE MESH DESIGN AND REGION-BASED DISCRETE WAVELET TRANSFORM." International Journal of Wavelets, Multiresolution and Information Processing 08, no. 03 (May 2010): 407–30. http://dx.doi.org/10.1142/s0219691310003559.

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Due to the large volume required for medical images for transmission and archiving purposes, the compression of medical images is known as one of the main concepts of medical image processing. Lossless compression methods have the drawback of a low compression ratio. In contrast, lossy methods have a higher compression ratio and suffer from lower quality of the reconstructed images in the receiver. Recently, some selective compression methods have been proposed in which the main image is divided into two separate regions: Region of Interest (ROI), which should be compressed in a lossless manner, and Region of Background (ROB), which is compressed in a lossy manner with a lower quality. In this research, we introduce a new selective compression method to compress 3D brain MR images. To this aim, we design an adaptive mesh on the first slice and estimate the gray levels of the next slices by computing the mesh element's deformations. After computing the residual image, which is the difference between the main image and the estimated one, we transform it to the wavelet domain using a region-based discrete wavelet transform (RBDWT). Finally, the wavelet coefficients are coded by an object-based SPIHT coder.

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Zhang, Ying, Yubin Zhu, Kaining Han, Junchao Wang, and Jianhao Hu. "A High-Accuracy Stochastic FIR Filter with Adaptive Scaling Algorithm and Antithetic Variables Method." Electronics 10, no. 16 (August 11, 2021): 1937. http://dx.doi.org/10.3390/electronics10161937.

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Digital filter is an important fundamental component in digital signal processing (DSP) systems. Among the digital filters, the finite impulse response (FIR) filter is one of the most commonly used schemes. As a low-complexity hardware implementation technique, stochastic computing has been applied to overcome the huge hardware cost problem of high-order FIR filters. However, the stochastic FIR filter (SFIR) scheme suffers from long processing latency and accuracy degradation. In this paper, the bit stream representation noise is theoretically analyzed, and an adaptive scaling algorithm (ASA) is proposed to improve the accuracy of SFIR with the same bit stream length. Furthermore, a novel antithetic variables method is proposed to further improve the accuracy. According to the simulation results on a 64-tap FIR filter, the ASA and AV methods gain 17 dB and 6 dB on the signal-to-noise ratio (SNR), respectively. The hardware implementation results are also presented in this paper, which illustrates that the proposed ASA-AV-SFIR filter increases 4.6 times hardware efficiency with respect to the existing SFIR schemes.

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HAYASHI, Naoki, Toshimitsu USHIO, and Takafumi KANAZAWA. "Adaptive Arbitration of Fair QoS Based Resource Allocation in Multi-Tier Computing Systems." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E93-A, no. 9 (2010): 1678–83. http://dx.doi.org/10.1587/transfun.e93.a.1678.

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Liu, Li, Tao Yao, Xin Hu, Chunjie Zhou, Dianli Hou, Shulin Feng, and Hongyong Yang. "Distributed State Estimation for Dynamic Positioning Systems with Uncertain Disturbances and Transmission Time Delays." Complexity 2020 (July 20, 2020): 1–15. http://dx.doi.org/10.1155/2020/7698504.

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The dynamic positioning system of unmanned underwater vehicles (UUVs) is a complex and large-scale system mainly due to the nonlinear dynamics, uncertainty in model parameters, and external disturbances. With the aid of the bio-inspired computing (BIC) method, the designed three-dimensional (3D) spatial positioning system is used for enlarging communication constraints and increasing signal coordination processing. With the growing of measurement scales, the issue of the networked high-precision positioning has been developed rapidly. Then, an information fusion estimation approach is presented for the distributed networked systems with data random transmission time delays and lost and disordered packets. To reduce the communication burden, an adaptive signal selection scheme is employed to reorganize the measurement sequence, and the parameter uncertainties as well as cross-correlated noise are used to describe the uncertain disturbances. Moreover, a reoptimal weighted fusion state estimation is designed to alleviate the information redundancy and maintain higher measurement accuracy. An illustrative example obtained from the 3D spatial positioning system is given to validate the effectiveness of the proposed method.

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Kohonen, T. "The Self-Organising Map, a Possible Model of Brain Maps." Perception 26, no. 1_suppl (August 1997): 204. http://dx.doi.org/10.1068/v970002.

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We stipulate that the following three categories of dynamic phenomena must be present in a realistic neural-network model: (i) activation; (ii) adaptation; (iii) plasticity control. In most neural models only activation and adaptation are present. The self-organising map (SOM) algorithm is the only neural-network model that includes all the three phenomena. Its modelling laws include the following partial functions: (1) Some parallel computing mechanism for the specification of a cell in a piece of cell mass whose parametric representation matches or responds best to the afferent input. This cell is called the ‘winner’. (2) Control of some learning factor in the cells in the neighbourhood of the ‘winner’ so that only this neighbourhood is adapted to the current input. By virtue of the ‘neighbourhood learning,’ the SOM forms spatially ordered maps of sensory experiences, which resemble the maps observed in the brain. The newest version of the SOM is the ASSOM (adaptive-subspace SOM). The adaptive processing units of ASSOM are able to represent signal subspaces, not just templates of the original patterns. A signal subspace is an invariance group; therefore the processing units of ASSOM are able to respond invariantly, eg to moving and transforming patterns, in a similar fashion as the complex cells in the cortex.

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Paez-Rueda, Carlos-Ivan, Arturo Fajardo, Manuel Pérez, and Gabriel Perilla. "Closed-Form Expressions for Numerical Evaluation of Self-Impedance Terms Involved on Wire Antenna Analysis by the Method of Moments." Electronics 10, no. 11 (May 30, 2021): 1316. http://dx.doi.org/10.3390/electronics10111316.

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This paper proposes new closed expressions of self-impedance using the Method of Moments with the Point Matching Procedure and piecewise constant and linear basis functions in different configurations, which allow saving computing time for the solution of wire antennas with complex geometries. The new expressions have complexity O(1) with well-defined theoretical bound errors. They were compared with an adaptive numerical integration. We obtain an accuracy between 7 and 16 digits depending on the chosen basis function and segmentation used. Besides, the computing time involved in the calculation of the self-impedance terms was evaluated and compared with the time required by the adaptative quadrature integration solution of the same problem. Expressions have a run-time bounded between 50 and 200 times faster than an adaptive numerical integration assuming full computation of all constant of the expressions.

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Huang, Yanquan, Haoliang Yuan, and Loi Lei Lai. "Latent multi-view semi-supervised classification by using graph learning." International Journal of Wavelets, Multiresolution and Information Processing 18, no. 05 (June 20, 2020): 2050039. http://dx.doi.org/10.1142/s0219691320500393.

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Multi-view learning is a hot research direction in the field of machine learning and pattern recognition, which is attracting more and more attention recently. In the real world, the available data commonly include a small number of labeled samples and a large number of unlabeled samples. In this paper, we propose a latent multi-view semi-supervised classification method by using graph learning. This work recovers a latent intact representation to utilize the complementary information of the multi-view data. In addition, an adaptive graph learning technique is adopted to explore the local structure of this latent intact representation. To fully use this latent intact representation to discover the label information of the unlabeled data, we consider to unify the procedures of computing the latent intact representation and the labels of unlabeled data as a whole. An alternating optimization algorithm is designed to effectively solve the optimization of the proposed method. Extensive experimental results demonstrate the effectiveness of our proposed method.

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Li, Xiaomin, Di Li, Jiafu Wan, Chengliang Liu, and Muhammad Imran. "Adaptive Transmission Optimization in SDN-Based Industrial Internet of Things With Edge Computing." IEEE Internet of Things Journal 5, no. 3 (June 2018): 1351–60. http://dx.doi.org/10.1109/jiot.2018.2797187.

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Samanta, Amit, and Zheng Chang. "Adaptive Service Offloading for Revenue Maximization in Mobile Edge Computing With Delay-Constraint." IEEE Internet of Things Journal 6, no. 2 (April 2019): 3864–72. http://dx.doi.org/10.1109/jiot.2019.2892398.

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Nakamura, Thiago A., Reinaldo M. Palhares, Walmir M. Caminhas, Benjamin R. Menezes, Mário Cesar M. M. de Campos, Ubirajara Fumega, Carlos H. de M. Bomfim, and André P. Lemos. "Adaptive fault detection and diagnosis using parsimonious Gaussian mixture models trained with distributed computing techniques." Journal of the Franklin Institute 354, no. 6 (April 2017): 2543–72. http://dx.doi.org/10.1016/j.jfranklin.2016.11.024.

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Daengdej, Jirapun, Pratit Santiprabhob, Hung T. Nguyen, and Vladik Kreinovich. "Selected Papers from InTech'05." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 10 (December 20, 2007): 1175–76. http://dx.doi.org/10.20965/jaciii.2007.p1175.

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The main objective of the annual International Conference on Intelligent Technologies (InTech) is to bring together researchers and practitioners who implement intelligent and fuzzy technologies in real-world environment. The Sixth International Conference on Intelligent Technologies InTech was held in Phuket, Thailand, on December 14-16, 2005. Topics of InTech'05 included mathematical foundations of intelligent technologies, traditional Artificial Intelligent techniques, uncertainty processing and methods of soft computing, learning/adaptive systems/data mining, and applications of intelligent technologies. This special issue contains extended versions of 11 selected papers originally presented at InTech'05. These papers cover most of the topics of the conference. Several papers describe intelligent applications of traditional data processing and signal processing techniques. H. Sawada et al. use advanced signal processing techniques to separate it sounds coming from different directions and thus, to enable user to it control robots by voice in noisy environments. N. Theera-Umpon uses a techniques of selecting a Region of Interest to enhance the behavior of the signal processing techniques when it detecting buried landmines. N. Shigei et al. describe innovative vector quantization technique which improve it image compression. T. A. Duong et al. use entropy approach to automatically it detect different it chemicals in the air. A few papers describe new applications of fuzzy and computing-with-words techniques. J. Han et al. describe how fuzzy it clustering techniques can be enhanced when we take into account that different factors may have different importance and thus, must be taken with different weights. J. Y. Zhang et al. show how fuzzy techniques – specifically, fuzzy causal models – can improve the efficiency of computer systems for it e-commerce. I. Kobayashi et al. use a new techniques (similar to computing with words) that helps to it personalize help for software users. Several papers take into account that in real life, knowledge is it hierarchical, and decision making and control are also hierarchical. T. H. Tran et al. show how a hierarchical combination of PID control with sliding-mode controllers can lead to robust non-overshoot high quality it control. L. Ding describes general challenges and ideas related to the need to take into account the hierarchical character of our knowledge. Finally, two papers deal with radically new approaches to intelligent data processing. Y. Murai et al. propose a new efficient method of it representing objects in space, a method in which an object A is described by “distance field” d(x) – describing the distance from an arbitrary point x to this object A. K. Akama et al. describe a new general computation model that is extremely useful in it checking program correctness. We want to thank all the authors for their outstanding work, the participants of InTech'05 for their helpful suggestions, the anonymous reviewers for their thorough analysis and constructive help, and – last but not the least – to Professor Kaoru Hirota for his kind suggestion to host this issue and to the entire staff of the journal for their tireless work.

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Ivanov, Rosen. "Accuracy analysis of BLE beacon-based localization in smart buildings." Journal of Ambient Intelligence and Smart Environments 13, no. 4 (July 21, 2021): 325–44. http://dx.doi.org/10.3233/ais-210607.

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The majority of services that deliver personalized content in smart buildings require accurate localization of their clients. This article presents an analysis of the localization accuracy using Bluetooth Low Energy (BLE) beacons. The aim is to present an approach to create accurate Indoor Positioning Systems (IPS) using algorithms that can be implemented in real time on platforms with low computing power. Parameters on which the localization accuracy mostly depends are analyzed: localization algorithm, beacons’ density, deployment strategy, and noise in the BLE channels. An adaptive algorithm for pre-processing the signals from the beacons is proposed, which aims to reduce noise in beacon’s data and to capture visitor’s dynamics. The accuracy of five range-based localization algorithms in different use case scenarios is analyzed. Three of these algorithms are specially designed to be less sensitive to noise in radio channels and require little computing power. Experiments conducted in a simulated and real environment show that using proposed algorithms the localization accuracy less than 1 m can be obtained.

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Asaad, Maha Salah, and Muayad Sadik Croock. "Adaptive security approach for wireless sensor network using RSA algorithm." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (April 1, 2021): 361. http://dx.doi.org/10.11591/ijeecs.v22.i1.pp361-368.

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A type of distributed and self-regulating network is the wireless sensor network (WSN). The sensor nodes have limited computing capabilities, memory, battery power are needed to ensure a strong security design. In this paper, an adaptive cryptographic scheme for WSN that is operating on routing ad hoc on-demand vector routing (AODV) protocol. The adaptive term refers to the adopted mechanism between heavy and light asymmetric cryptography techniques of RSA. The heavy technique adopts the complete version of RSA algorithm, while the light one considers a reduced complexity version. This is to control the security operation over the included nodes even with low power ratio. In various case studies, the proposed scheme is checked and the result obtained shows the high efficiency of results in terms of protection guarantee.

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P, Vijaya, and Binu D. "Introduction to the Special Issue on Intelligence on Scalable computing for Recent Applications." Scalable Computing: Practice and Experience 21, no. 2 (June 27, 2020): 157–58. http://dx.doi.org/10.12694/scpe.v21i2.1581.

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The special issue has been focussed to overcome the challenges of scalability, which includes size scalability, geographical scalability, administrative scalability, network and synchronous communication limitation, etc.The challenges also emerge with the development of recent applications. Hence this proposal has been planned to handle the scalability issues in recent applications. This special issue invites researchers, engineers, educators, managers, programmers, and users of computers who have particular interests in parallel processing and/or distributed computing and artificial intelligence to submit original research papers and timely review articles on the theory, design, evaluation, and use of artificial intelligence and parallel and/or distributed computing systems for emerging applications. The ten papers in this special issue cover a range of aspects of theoretical and practical research development on scalable computing. The proposal provides an effective forum for communication among researchers and practitioners from various scientific areas working in a wide variety of problem areas, sharing a fundamental common interest in improving the ability of parallel and distributed computer systems, intelligent techniques, and deep learning mechanisms and advanced soft computing techniques. The issue covers wide range of applications, but with scalable problems that to be solved by perfect hybridization of distributed computing and artificial intelligence.The first paper is “CPU-Memory Aware VM Consolidation for Cloud Data Centers” introduced a CPU Memory aware VM placement algorithm is proposed for selecting suitable destination host for migration. The Virtual Machines are selected using Fuzzy Soft Set (FSS) method VM selection algorithm. The proposed placement algorithm considers CPU, Memory, and combination of CPU-Memory utilization of VMs on the source host.In “Bird Swarm Optimization-based stacked autoencoder deep learning for umpire detection and classification”, presented the umpire detection and classification by proposing an optimization algorithm. The overall procedure of the proposed approach involves three steps, like segmentation, feature extraction, and classification. Here, the classification is done using the proposed Bird Swarm Optimization-based stacked autoencoder deep learning classifier (BSO-Stacked Autoencoders), that categories into umpire or others.In “Enhanced DBSCAN with Hierarchical tree for Web Rule Mining”, proposed an enhanced web mining model based on two contributions. At first, the hierarchical tree is framed, which produces different categories of the searching queries (different web pages). Next, to hierarchical tree model, enhanced Density-Based Spatial Clustering of Applications with Noise (DBSCAN) technique model is developed by modifying the traditional DBSCAN. This technique results in proper session identification from raw data. Moreover, this technique offers the optimal level of clusters necessitated for hierarchical clustering. After hierarchical clustering, the rule mining is adopted. The traditional rule mining technique is generally based on the frequency; however, this paper intends to enhance the traditional rule mining based on utility factor as the second contribution. Hence the proposed model for web rule mining is termed as Enhanced DBSCAN-based Hierarchical Tree (EDBHT).In “A comprehensive survey of the Routing Schemes for IoT applications”, this review article provides a detailed review of 52 research papers presenting the suggested routing protocols based on the content-based, clustering-based, fuzzy-based, Routing Protocol for Low power (RPL) and Lossy Networks, tree-based and soon. Also, a detailed analysis and discussion are made by concerning the parameters, simulation tool, and year of publication, network size, evaluation metrics, and utilized protocols. In “Chicken-Moth Search Optimization-Based Deep Convolutional Neural Network For Image Steganography”, proposed an effective pixel prediction based on image stegonography is developed, which employs error dependent Deep Convolutional Neural Network (DCNN) classifier for pixel identification. Here, the best pixels are identified from the medical image based on DCNN classifier using pixel features, like texture, wavelet energy, Gabor, scattering features, and so on. The DCNN is optimally trained using Chicken-Moth search optimization (CMSO). The CMSO is designed by integrating Chicken Swarm Optimization (CSO) and Moth Search Optimization (MSO) algorithm based on limited error.In “An Efficient Dynamic Slot Scheduling Algorithm for WSN MAC: A Distributed Approach”, an effective TDMA based slot scheduling algorithm needs to be designed. In this paper, we propose a TDMA based algorithm named DYSS that meets both the timeliness and energy efficiency in handling the collision. This algorithm finds an effective way of preparing the initial schedule by using the average two-hop neighbors count. Finally, the remaining un-allotted nodes are dynamically assigned to slots using a novel approach.In “Artefacts removal from ECG Signal: Dragonfly optimization-based learning algorithm for neural network-enhanced adaptive filtering”, proposed a method utilizes the adaptive filter termed as the (Dragonfly optimization + Levenberg Marqueret learning algorithm) DLM-based Nonlinear Autoregressive with eXogenous input (NARX) neural network for the removal of the artefacts from the ECG signals. Once the artefact signal is identified using the adaptive filter, the identified signal is subtracted from the primary signal that is composed of the ECG signal and the artefacts through an adaptive subtraction procedure.In “A Comprehensive Review on State-of-the-Art Image Inpainting Techniques”, this survey makes a critical analysis of diverse techniques regarding various image inpainting schemes. This paper goes under (i) Analyzing various image inpainting techniques that are contributed in different papers. (ii) Makes the comprehensive study regarding the performance measures and the corresponding maximum achievements in each contribution. (iii) Analytical review concerning the chronological review and various tools exploited in each of the reviewed works.In “An Efficient Way of Finding Polarity of Roman Urdu Reviews by Using Boolean Rules”, proposed a novel approach by using Boolean rules for the identification of the related and non-related comments. Related reviews are those which show the behavior of a customer about a particular product. Lexicons are built for the identification of noise, positive and negative reviews.The final paper is “Forecasting the Impact of Social Media Advertising among College Students using Higher Order Statistical Functions”, this research work plans to develop a statistical review that concerns on social media advertising among college students from diverse universities. The review analysis on social media advertising is given under six sections such as: (i) Personal Profile; (ii) Usage; (iii) Assessment; (iv) Higher Order statistics like Community, Connectedness, Openness, Dependence, and Participation; (v) Trustworthiness such as Trust, Perceived value and Perceived risk; and (vi) Towards advertisement which involves attitude towards advertisement, response towards advertisement and purchase intension.

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Markevicius, Navikas, Idzkowski, Miklusis, Andriukaitis, Valinevicius, Zilys, Cepenas, and Walendziuk. "Vehicle Speed and Length Estimation Errors Using the Intelligent Transportation System with a Set of Anisotropic Magneto-Resistive (AMR) Sensors." Sensors 19, no. 23 (November 28, 2019): 5234. http://dx.doi.org/10.3390/s19235234.

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Seeking an effective method for estimating the speed and length of a car is still a challenge for engineers and scientists who work on intelligent transportation systems. This paper focuses on a self-developed system equipped with four anisotropic magneto-resistive (AMR) sensors which are placed on a road lane. The piezoelectric polyvinylidene fluoride (PVDF) sensors are also mounted and used as a reference device. The methods applied in the research are well-known: the fixed threshold-based method and the adaptive two-extreme-peak detection method. However, the improved accuracy of estimating the length by using one of the methods, which is based on computing the difference quotient of a time-discrete signal (representing the changes in the magnitude of the magnetic field of the Earth), is observed. The obtained results, i.e., the speed and length of a vehicle, are presented for various values of the increment Δn used in numerical differentiation of magnetic field magnitude data. The results were achieved in real traffic conditions after analyzing a data set M = 290 of vehicle signatures. The accuracy was evaluated by calculating MAE (Mean Absolute Error), RMSE (Root Mean Squared Error) for different classes of vehicles. The MAE is within the range of 0.52 m–1.18 m when using the appropriate calibration factor. The results are dependent on the distance between sensors, the speed of vehicle and the signal processing method applied.

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Czarnul, Paweł. "Assessment of OpenMP Master–Slave Implementations for Selected Irregular Parallel Applications." Electronics 10, no. 10 (May 16, 2021): 1188. http://dx.doi.org/10.3390/electronics10101188.

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The paper investigates various implementations of a master–slave paradigm using the popular OpenMP API and relative performance of the former using modern multi-core workstation CPUs. It is assumed that a master partitions available input into a batch of predefined number of data chunks which are then processed in parallel by a set of slaves and the procedure is repeated until all input data has been processed. The paper experimentally assesses performance of six implementations using OpenMP locks, the tasking construct, dynamically partitioned for loop, without and with overlapping merging results and data generation, using the gcc compiler. Two distinct parallel applications are tested, each using the six aforementioned implementations, on two systems representing desktop and worstation environments: one with Intel i7-7700 3.60 GHz Kaby Lake CPU and eight logical processors and the other with two Intel Xeon E5-2620 v4 2.10 GHz Broadwell CPUs and 32 logical processors. From the application point of view, irregular adaptive quadrature numerical integration, as well as finding a region of interest within an irregular image is tested. Various compute intensities are investigated through setting various computing accuracy per subrange and number of image passes, respectively. Results allow programmers to assess which solution and configuration settings such as the numbers of threads and thread affinities shall be preferred.

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23

Cowan, C. F. N., R. F. Woods, J. P. Heron, P. Power, and F. J. Sweeney. "Advances in adaptive signal processing: totally adaptive systems." Annual Reviews in Control 25 (January 2001): 55–64. http://dx.doi.org/10.1016/s1367-5788(01)00006-2.

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Cowan, C. F. N., R. F. Woods, J. P. Heron, P. Power, and F. J. Sweeney. "Advances in Adaptive Signal Processing: Totally Adaptive Systems." IFAC Proceedings Volumes 31, no. 22 (August 1998): 185–94. http://dx.doi.org/10.1016/s1474-6670(17)35941-4.

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Plataniotis, K. N., D. Androutsos, and A. N. Venetsanopoulos. "Adaptive fuzzy systems for multichannel signal processing." Proceedings of the IEEE 87, no. 9 (1999): 1601–22. http://dx.doi.org/10.1109/5.784243.

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26

Brookner, E. "Radar signal processing and adaptive systems [Book Review]." IEEE Aerospace and Electronic Systems Magazine 15, no. 9 (September 2000): 47. http://dx.doi.org/10.1109/maes.2000.873478.

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Chen, Walter Y., and Richard A. Haddad. "Dual mode adaptive signal processing." Computers & Electrical Engineering 18, no. 3-4 (May 1992): 261–75. http://dx.doi.org/10.1016/0045-7906(92)90019-a.

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28

Bitmead, Robert R., C. Richard Johnson, and Clifford R. Pollock. "Optical adaptive signal processing: An appraisal." International Journal of Adaptive Control and Signal Processing 5, no. 2 (March 1991): 87–92. http://dx.doi.org/10.1002/acs.4480050202.

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Orosz, György, László Sujbert, and Gábor Péceli. "Synchronization and sampling in wireless adaptive signal processing systems." Periodica Polytechnica Electrical Engineering 54, no. 1-2 (2010): 59. http://dx.doi.org/10.3311/pp.ee.2010-1-2.06.

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Qaisar, Saeed Mian. "Efficient mobile systems based on adaptive rate signal processing." Computers & Electrical Engineering 79 (October 2019): 106462. http://dx.doi.org/10.1016/j.compeleceng.2019.106462.

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Etter, Delores M. "An introduction to adaptive signal processing." Computers & Electrical Engineering 18, no. 3-4 (May 1992): 189–93. http://dx.doi.org/10.1016/0045-7906(92)90013-4.

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32

Grydeland, T., F. D. Lind, P. J. Erickson, and J. M. Holt. "Software Radar signal processing." Annales Geophysicae 23, no. 1 (January 31, 2005): 109–21. http://dx.doi.org/10.5194/angeo-23-109-2005.

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Abstract. Software infrastructure is a growing part of modern radio science systems. As part of developing a generic infrastructure for implementing Software Radar systems, we have developed a set of reusable signal processing components. These components are generic software-based implementations for use on general purpose computing systems. The components allow for the implementation of signal processing chains for radio frequency signal reception, correlation-based data processing, and cross-correlation-based interferometry. The components have been used to implement the signal processing necessary for incoherent scatter radar signal reception and processing as part of the latest version of the Millstone Hill Data Acquisition System (MIDAS-W). Several hardware realizations with varying capabilities have been created, and these have been used successfully with different radars. We discuss the signal processing components in detail, describe the software patterns in which they are used, and show example data from the Millstone Hill, EISCAT Svalbard, and SOUSY Svalbard radars.

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33

Melkas, Kaarina. "Optical signal processing, computing and neural networks." Signal Processing 35, no. 1 (January 1994): 100. http://dx.doi.org/10.1016/0165-1684(94)90200-3.

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Chen, Junlin, and Lei Wang. "Energy-Adaptive Signal Processing Under Renewable Energy." Journal of Signal Processing Systems 84, no. 3 (November 2, 2015): 399–412. http://dx.doi.org/10.1007/s11265-015-1071-8.

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35

Kadlec, Jir̆í. "Adaptive system identification and signal processing algorithms." Automatica 31, no. 10 (October 1995): 1519–21. http://dx.doi.org/10.1016/0005-1098(95)90000-4.

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36

Naik, Sanjeev. "Advanced misfire detection using adaptive signal processing." International Journal of Adaptive Control and Signal Processing 18, no. 2 (March 2004): 181–98. http://dx.doi.org/10.1002/acs.789.

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37

Haykin, S. "Lessons on adaptive systems for signal processing, communications, and control." IEEE Signal Processing Magazine 16, no. 5 (September 1999): 39–48. http://dx.doi.org/10.1109/msp.1999.790980.

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38

Giancarlo, C., and C. Sodini. "A slope adaptive delta modulator for VLSI signal processing systems." IEEE Transactions on Circuits and Systems 33, no. 1 (January 1986): 51–58. http://dx.doi.org/10.1109/tcs.1986.1085833.

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39

Sudha, Danthuluri, and Sanjay Chitnis. "An energy optimization with improved QOS approach for adaptive cloud resources." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 5 (October 1, 2020): 4881. http://dx.doi.org/10.11591/ijece.v10i5.pp4881-4891.

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In recent times, the utilization of cloud computing VMs is extremely enhanced in our day-to-day life due to the ample utilization of digital applications, network appliances, portable gadgets, and information devices etc. In this cloud computing VMs numerous different schemes can be implemented like multimedia-signal-processing-methods. Thus, efficient performance of these cloud-computing VMs becomes an obligatory constraint, precisely for these multimedia-signal-processing-methods. However, large amount of energy consumption and reduction in efficiency of these cloud-computing VMs are the key issues faced by different cloud computing organizations. Therefore, here, we have introduced a dynamic voltage and frequency scaling (DVFS) based adaptive cloud resource re-configurability (ACRR) technique for cloud computing devices, which efficiently reduces energy consumption, as well as perform operations in very less time. We have demonstrated an efficient resource allocation and utilization technique to optimize by reducing different costs of the model. We have also demonstrated efficient energy optimization techniques by reducing task loads. Our experimental outcomes shows the superiority of our proposed model ACRR in terms of average run time, power consumption and average power required than any other state-of-art techniques.

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Ksendzuk, A. V., and K. O. Kozlov. "ADAPTIVE CORRELATOR IN NON-EMITTING RADAR SYSTEMS." Issues of radio electronics, no. 3 (March 20, 2019): 41–45. http://dx.doi.org/10.21778/2218-5453-2019-3-41-45.

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The paper discusses a new method of processing information in non‑emitting radar systems, whose work is based on the use of a signal from third‑party sources – television and radio broadcasting transmitters, as well as cellular base stations. An adaptive correlator for such radar stations is proposed. The method is based on the analysis of the autocorrelation function (ACF) of a transmitter signal and the adaptive formation of detection areas, based on the properties of the current ACF. Statistical quality parameters were introduced to evaluate the developed method and these parameters were estimated for the DVB‑T2 (Digital Video Broadcasting – Terrestrial) signal, in particular, the achievable characteristics by the side lobes of the lag time uncertainty function for such a signal are shown. It is noted that several adaptive correlators should be simultaneously implemented in non‑radiant radar. The results of processing real data confirm the effectiveness of the proposed method.

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Shojafar, Mohammad, Claudia Canali, Riccardo Lancellotti, and Jemal Abawajy. "Adaptive Computing-Plus-Communication Optimization Framework for Multimedia Processing in Cloud Systems." IEEE Transactions on Cloud Computing 8, no. 4 (October 1, 2020): 1162–75. http://dx.doi.org/10.1109/tcc.2016.2617367.

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Shah, Syed M., R. Samar, N. M. Khan, and M. A. Z. Raja. "Fractional-order adaptive signal processing strategies for active noise control systems." Nonlinear Dynamics 85, no. 3 (April 5, 2016): 1363–76. http://dx.doi.org/10.1007/s11071-016-2765-6.

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43

Rude, Michael J. "A robust algorithm for untrained adaptive signal processing." Computers & Electrical Engineering 18, no. 3-4 (May 1992): 205–16. http://dx.doi.org/10.1016/0045-7906(92)90015-6.

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El-Mahdy, Ahmed El-Sayed. "Adaptive Selection Combining Receiver over Time Varying Frequency Selective Fading Channel in Class-A Noise." ISRN Signal Processing 2013 (May 13, 2013): 1–6. http://dx.doi.org/10.1155/2013/894542.

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An adaptive selection combining (SC) scheme is proposed for time varying mobile communication channel in Class-A impulsive noise. The receiver adaptively selects a diversity branch out of the available branches and discards the others. This is performed by computing the maximum likelihood (ML) metric of each diversity branch and selects the branch with the maximum metric. The proposed adaptive SC scheme dynamically adjusts the threshold value according to the time variations of the channel. Equalization and data detection are performed after combining using maximum likelihood sequence estimation implemented by Viterbi algorithm (MLSE-VA). The minimum survivor technique is employed to reduce the complexity of the receiver.

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45

Berman, F., R. Wolski, H. Casanova, W. Cirne, H. Dail, M. Faerman, S. Figueira, et al. "Adaptive computing on the grid using AppLeS." IEEE Transactions on Parallel and Distributed Systems 14, no. 4 (April 2003): 369–82. http://dx.doi.org/10.1109/tpds.2003.1195409.

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46

Gaydecki, Patrick. "The Foundations of Digital Signal Processing Using Signal Wizard Systems®." International Journal of Electrical Engineering & Education 49, no. 3 (July 2012): 310–20. http://dx.doi.org/10.7227/ijeee.49.3.10.

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Signal Wizard Systems® is a digital signal processing (DSP) research venture within the School of EEE at the University of Manchester, UK. It specialises in the development and supply of real-time DSP products for audio signal analysis and processing. The unique and underpinning philosophy of these products is their ease of use. The systems require minimal knowledge of DSP theory on the part of the user and none of the mathematics associated with digital filter design. Filters and other algorithms can be designed in seconds, downloaded and executed in real time with just a few mouse clicks. Since 2004 Signal Wizard products have been sold all over the world for applications ranging from noise suppression, adaptive filtering and system modelling to musical instrument research. In particular, their ease of use ensures that they are ideally suited for teaching simple and more advanced concepts in DSP both at undergraduate and postgraduate level. For this purpose, a DSP laboratory teaching package has been developed using the Signal Wizard range of devices, and has proven an invaluable tool for training our student cohort in the practical aspects of DSP engineering design and programming.

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47

Leung, H., T. Lo, and J. Litva. "Nonlinear adaptive signal processing based on rational function." Signal Processing 38, no. 2 (July 1994): 153–68. http://dx.doi.org/10.1016/0165-1684(94)90136-8.

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48

Xia, Saiqiang, Jun Yang, Wanyong Cai, Chaowei Zhang, Liangfa Hua, and Zibo Zhou. "Adaptive Complex Variational Mode Decomposition for Micro-Motion Signal Processing Applications." Sensors 21, no. 5 (February 26, 2021): 1637. http://dx.doi.org/10.3390/s21051637.

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In order to suppress the strong clutter component and separate the effective fretting component from narrow-band radar echo, a method based on complex variational mode decomposition (CVMD) is proposed in this paper. The CVMD is extended from variational mode decomposition (VMD), which is a recently introduced technique for adaptive signal decomposition, limited to only dealing with the real signal. Thus, the VMD is extended from the real domain to the complex domain firstly. Then, the optimal effective order of singular value is obtained by singular value decomposition (SVD) to solve the problem of under-decomposition or over-decomposition caused by unreasonable choice of decomposition layer, it is more accurate than detrended fluctuation analysis (DFA) and empirical mode decomposition (EMD). Finally, the strongly correlated modes and weakly correlated modes are judged by calculating the Mahalanobis distance between the band-limited intrinsic mode functions (BLIMFs) and the original signal, which is more robust than the correlation judgment methods such as computing cross-correlation, Euclidean distance, Bhattachryya distance and Hausdorff distance. After the weak correlation modes are eliminated, the signal is reconstructed locally, and the separation of the micro-motion signal is realized. The experimental results show that the proposed method can filter out the strong clutter component and the fuselage component from radar echo more effectively than the local mean decomposition (LMD), empirical mode decomposition and moving target indicator (MTI) filter.

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Zhang, Hongbing. "Application Research of Speech Signal Processing Technology Based on Cloud Computing Platform." International Journal of Information Technologies and Systems Approach 14, no. 2 (July 2021): 20–37. http://dx.doi.org/10.4018/ijitsa.2021070102.

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In recent years, in the context of the rapid development of information technology, artificial intelligence has also developed. People have begun to train machines. Many machines have been able to gradually understand human languagesand perform a series of actions based on language instructions. On this basis, scientific researchers hope that the machine can be more intelligent and humane. In the noise estimation stage, a noise estimation algorithm based on speech detection is used to effectively estimate the noise. Secondly, according to the characteristics of the method of speech noise reduction processing, a method of processing speech noise is realized. Finally, simulation experiments are used to illustrate the effectiveness of the algorithm. Aiming at the shortcomings of traditional speech noise reduction algorithms, improvements were made in adaptive filter estimation. The model's speech noise reduction algorithm was obtained. The cepstrum estimation of speech signals was modified, and the effect of speech enhancement was significantly improved.

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KRUK, Rafał, and Zbigniew REMPAŁA. "Monitor for Anti-Aircraft Guidance and Observation Systems." Problems of Mechatronics Armament Aviation Safety Engineering 10, no. 2 (June 30, 2019): 143–50. http://dx.doi.org/10.5604/01.3001.0013.2121.

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The paper presents a discussion on the issue of possible acceleration of radiolocation signal processing algorithms in seekers using graphics processing units. A concept and implementation examples of algorithms performing digital data filtering on general purpose central and graphics processing units are introduced. The results of performance comparison of central and graphics processing units during computing discrete convolution are presented at the end of the paper.

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