Relevant bibliographies by topics / Method backward propagation algorithm

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Method backward propagation algorithm'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Method backward propagation algorithm"

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Li, Jinze, Kaiping Yu, and Hong Tang. "Further Assessment of Three Bathe Algorithms and Implementations for Wave Propagation Problems." International Journal of Structural Stability and Dynamics 21, no. 05 (2021): 2150073. http://dx.doi.org/10.1142/s0219455421500735.

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This paper further analyzes three Bathe algorithms ([Formula: see text]-Bathe, [Formula: see text]-Bathe and [Formula: see text]-Bathe) with their unknown properties revealed. The analysis shows firstly that three Bathe algorithms can cover two common integration schemes, trapezoidal rule and backward Euler formula, and that the second-order [Formula: see text]-Bathe algorithm is algebraically identical to the [Formula: see text]-Bathe algorithm. Via formulation of the generalized two-sub-step Newmark algorithm, it is shown that the common Newmark method cannot be considered as a special case
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Felix, A. Pyatakovich* Lubov V. Khlivnenko Tatyana I. Yakunchenko Kristina F. Makkonen Olga V. Mevsha. "A COMPARATIVE ANALYSIS OF THE RESULTS OF CONVENTIONAL AND COMBINED METHODS OF TRAINING DIRECT PROPAGATION NEURAL NETWORK IN HEALTHY PERSONS TO DETECTING THE DEGREE OF ACTIVITY OF AN AUTONOMOUS NERVOUS SYSTEM." Indo American Journal of Pharmaceutical Sciences 04, no. 09 (2017): 3075–79. https://doi.org/10.5281/zenodo.910741.

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The article deals with a comparative analysis of the efficiency of an artificial neural network (ANN) trained with the help of algorithm back propagation, and of that trained by combining a back propagation algorithm and a variant of Cauchy stochastic training, in detecting the degree of activity of an autonomous nervous system. For the purposes realization of the project has been developed a biotechnical system, including technical device for input electrophysiological information in mode on-line. To evaluate the clinical effectiveness of the classification, records of interpulse intervals in
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Zhao, Changtong, Jie Ma, Wenshen Jia, et al. "An Apple Fungal Infection Detection Model Based on BPNN Optimized by Sparrow Search Algorithm." Biosensors 12, no. 9 (2022): 692. http://dx.doi.org/10.3390/bios12090692.

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To rapidly detect whether apples are infected by fungi, a portable electronic nose was used in this study to collect the gas information from apples, and the collected information was processed by smoothing filtering, data dimensionality reduction, and outlier removal. Following this, we utilized K-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), a convolutional neural network (CNN), a back-propagation neural network (BPNN), a particle swarm optimization–back-propagation neural network (PSO-BPNN), a gray wolf optimization–backward propagation neural network (GWO-BPNN)
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Lisitsyna, Liubov, Marina Senchilo, and Sergei Teleshev. "CREATING RLCP-COMPATIBLE VIRTUAL LABORATORIES FOR TRAINING BASIC ALGORITHMS ON NEURAL NETWORKS." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2021, no. 3 (2021): 134–42. http://dx.doi.org/10.24143/2072-9502-2021-3-134-142.

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The article describes the principles of developing RLCP-compatible virtual laboratories. There are build two virtual laboratories based on these principles for mastering the basic algo-rithms on neural networks: Algorithm for Sequential Signal Propagation in Perceptron and Algorithm for Training Perceptron Using Method of Backward Error Propagation. Virtual laboratories consist of two independent modules – a virtual stand and an RLCP server. The virtual stand implements a visual display of the task's data and provides the listener with tools for forming and editing intermediate solutions and r
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Hwang, Taewook, Hyein Seo, and Sangkeun Jung. "Local Back-Propagation for Forward-Forward Networks: Independent Unsupervised Layer-Wise Training." Applied Sciences 15, no. 15 (2025): 8207. https://doi.org/10.3390/app15158207.

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Recent deep learning models, including GPT-4, have achieved remarkable performance using the back-propagation (BP) algorithm. However, the mechanism of BP is fundamentally different from how the human brain processes learning. To address this discrepancy, the Forward-Forward (FF) algorithm was introduced. Although FF enables deep learning without backward passes, it suffers from instability, dependence on artificial input construction, and limited generalizability. To overcome these challenges, we propose Local Back-Propagation (LBP), a method that integrates layer-wise unsupervised learning w
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Shperberg, Shahaf, Ariel Felner, Solomon Shimony, Nathan Sturtevant, and Avi Hayoun. "Improving Bidirectional Heuristic Search by Bounds Propagation." Proceedings of the International Symposium on Combinatorial Search 10, no. 1 (2021): 106–14. http://dx.doi.org/10.1609/socs.v10i1.18508.

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Recent work in bidirectional heuristic search characterize pairs of nodes from which at least one node must be expanded in order to ensure optimality of solutions. We use these findings to propose a method for improving existing heuristics by propagating lower bounds between the forward and backward frontiers. We then define a number of desirable properties for bidirectional heuristic search algorithms, and show that applying the bound propagations adds these properties to many existing algorithms (e.g. to the MM family of algorithms). Finally, experimental results show that applying these pro
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Брыкин, В. В., М. Я. Брагинский, Д. В. Тараканов, and И. Л. Назарова. "CLASSIFYING PLANTS’ HEALTH USING AN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS)." Proceedings in Cybernetics 23, no. 2 (2024): 23–30. http://dx.doi.org/10.35266/1999-7604-2024-2-3.

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The study classifi es eight types of plants’ diseases using an adaptive neuro-fuzzy inference system (ANFIS). Haralick texture features obtained from plants’ images are applied as input data for a system. A hybrid algorithm consisting of a backward propagation of error and a gradient descent performed the ANFIS training. The ANFIS effi ciency was assessed on a test set through calculating accuracy, comprehensiveness, and the F1 score. The indicators obtained by this method were compared with other modern classifi cation methods.
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WANG, SHILONG, FEI ZHENG, and LING XU. "COMPARISON BETWEEN PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM IN ARTIFICIAL NEURAL NETWORK FOR LIFE PREDICTION OF NC TOOLS." Journal of Advanced Manufacturing Systems 07, no. 01 (2008): 1–7. http://dx.doi.org/10.1142/s0219686708001073.

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Accurate life prediction of NC (Numeric Control) tools is very essential in an advanced manufacturing system. In this paper, tool life prediction in a drilling process was researched. An Artificial Neural Network (ANN) has been established for prediction, with drill diameter, cutting speed and feed rate as input parameters and tool life as an output parameter. To improve the performance of the network, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were applied independently to train the network instead of standard Backward Propagation (BP) algorithm, which has drawbacks of low c
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Zhang, Bolun, Guangen Gao, and Yongxin Gao. "Cooperative Localization Based on Augmented State Belief Propagation for Mobile Agent Networks." Electronics 11, no. 13 (2022): 1959. http://dx.doi.org/10.3390/electronics11131959.

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Belief propagation (BP) is widely used to solve the cooperative localization problem due to its excellent performance and natural distributed structure of implementation. For a mobile agent network, its factor graph inevitably encounters loops. In this case, the BP algorithm becomes iterative and can only provide an approximate marginal probability density function of the estimate with finite iterations. We propose an augmented-state BP algorithm for mobile agent networks to alleviate the effect of loops. By performing state augmentation, the messages in the factor graph will actually be allow
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Yang, Pengliang, Romain Brossier, Ludovic Métivier, and Jean Virieux. "Wavefield reconstruction in attenuating media: A checkpointing-assisted reverse-forward simulation method." GEOPHYSICS 81, no. 6 (2016): R349—R362. http://dx.doi.org/10.1190/geo2016-0082.1.

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Three-dimensional implementations of reverse time migration (RTM) and full-waveform inversion (FWI) require efficient schemes to access the incident field to apply the imaging condition of RTM or build the gradient of FWI. Wavefield reconstruction by reverse propagation using final snapshot and saved boundaries appears quite efficient but unstable in attenuating media, whereas the checkpointing strategy is a stable alternative at the expense of increased computational cost through repeated forward modeling. We have developed a checkpointing-assisted reverse-forward simulation (CARFS) method in
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Dissertations / Theses on the topic "Method backward propagation algorithm"

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Ono, Sashi, and Hua Lee. "OBJECT RECOGNITION BY GROUND-PENETRATING RADAR IMAGING SYSTEMS WITH TEMPORAL SPECTRAL STATISTICS." International Foundation for Telemetering, 2004. http://hdl.handle.net/10150/604925.

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International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California<br>This paper describes a new approach to object recognition by using ground-penetrating radar (GPR) imaging systems. The recognition procedure utilizes the spectral content instead of the object shape in traditional methods. To produce the identification feature of an object, the most common spectral component is obtained by singular value decomposition (SVD) of the training sets. The identification process is then integrated into the backward propagation image reconstruc
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Alhossen, Iman. "Méthode d'analyse de sensibilité et propagation inverse d'incertitude appliquées sur les modèles mathématiques dans les applications d'ingénierie." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30314/document.

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Dans de nombreuses disciplines, les approches permettant d'étudier et de quantifier l'influence de données incertaines sont devenues une nécessité. Bien que la propagation directe d'incertitudes ait été largement étudiée, la propagation inverse d'incertitudes demeure un vaste sujet d'étude, sans méthode standardisée. Dans cette thèse, une nouvelle méthode de propagation inverse d'incertitude est présentée. Le but de cette méthode est de déterminer l'incertitude d'entrée à partir de données de sortie considérées comme incertaines. Parallèlement, les méthodes d'analyse de sensibilité sont égalem
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Westin, Robin. "Three material decomposition in dual energy CT for brachytherapy using the iterative image reconstruction algorithm DIRA : Performance of the method for an anthropomorphic phantom." Thesis, Linköpings universitet, Institutionen för medicinsk teknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-91297.

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Brachytherapy is radiation therapy performed by placing a radiation source near or inside a tumor. Difference between the current water-based brachytherapy dose formalism (TG-43) and new model based dose calculation algorithms (MBSCAs) can differ by more than a factor of 10 in the calculated doses. There is a need for voxel-by-voxel cross-section assignment, ideally, both the tissue composition and mass density of every voxel should be known for individual patients. A method for determining tissue composition via three material decomposition (3MD) from dual energy CT scans was developed at Lin
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Drissi, Mohamed. "Un modèle de propagation de feux de végétation à grande échelle." Thesis, Aix-Marseille, 2013. http://www.theses.fr/2013AIXM4704.

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Le présent travail est consacré au développement et à la validation d'un modèle hybride de propagation d'un incendie de végétation à grande échelle prenant en compte les hétérogénéités locales liées à la végétation, à la topographie du terrain et aux conditions météorologiques. Dans un premier temps, on présente différentes méthodes permettant de générer un réseau amorphe, représentatif d'une distribution réaliste de la végétation. Le modèle hybride est un modèle de réseau où les phénomènes qui se produisent à l'échelle macroscopique sont traités de façon déterministe, comme le préchauffage du
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Taminato, Filipe Otsuka. "Aperfeiçoamento do algoritmo algébrico sequencial para a identificação de variações abruptas de impedância acústica via otimização." Universidade do Estado do Rio de Janeiro, 2014. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=6834.

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Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro<br>Neste trabalho são utilizados a técnica baseada na propagação de ondas acústicas e o método de otimização estocástica Luus-Jaakola (LJ) para solucionar o problema inverso relacionado à identificação de danos em barras. São apresentados o algoritmo algébrico sequencial (AAS) e o algoritmo algébrico sequencial aperfeiçoado (AASA) que modelam o problema direto de propagação de ondas acústicas em uma barra. O AASA consiste nas modificações introduzidas no AAS. O uso do AASA resolve com vantagens o problema de identifi
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Hunter, Brandon. "Channel Probing for an Indoor Wireless Communications Channel." BYU ScholarsArchive, 2003. https://scholarsarchive.byu.edu/etd/64.

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The statistics of the amplitude, time and angle of arrival of multipaths in an indoor environment are all necessary components of multipath models used to simulate the performance of spatial diversity in receive antenna configurations. The model presented by Saleh and Valenzuela, was added to by Spencer et. al., and included all three of these parameters for a 7 GHz channel. A system was built to measure these multipath parameters at 2.4 GHz for multiple locations in an indoor environment. Another system was built to measure the angle of transmission for a 6 GHz channel. The addition of th
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Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.

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Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, i
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Liang, Shu-fang, and 梁淑芳. "A Parallel Back-Propagation Algorithm with the Levenberg Marquardt Method." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/18644310071227714685.

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碩士<br>東吳大學<br>資訊科學系<br>94<br>Due to the excellent learning capability of the artificial neural network (ANN), many researches are interesting in using it to solve problems in pattern recognition, cluster analysis, forecasting, etc. The ANN applications have been approved by many specialists and scholars from many fields of science. It's knows by practical application, ANN manipulates different learn rules, it’s disappear speed, variance and learn time, there are obvious differences. Among the supervised networks, the Back Propagation Network (BPN) model is the most popular and it is the basis
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Pear, Huang, and 黃宗慶. "Improvement of Back Propagation Algorithm by Error Saturation Prevention Method." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/28527021447087639836.

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碩士<br>國立臺灣科技大學<br>電子工程技術研究所<br>86<br>Back Propagation algorithm is currently the most widely used learning algorithm in artificial neural networks. With properly selection of feed-forward neural network architecture, it is capable of approximating most problems with high accuracy and generalization ability. However, the slow convergence is a serious problem when using this well-known Back Propagation (BP) learning algorithm in many applications. As a result, many researchers take effort to improve the learning efficiency of BP algorithm by various enhancements. In our study, we consider th
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Ko, Jia-Hui, and 柯佳蕙. "Medical Image Classifier with a Priori Clustering Method Using Affinity Propagation Algorithm." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/70222139787027209188.

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碩士<br>慈濟大學<br>醫學資訊學系碩士班<br>101<br>Computed tomography (CT) is the most common imaging technique in clinic. With an intravenous contrast agent, more anatomical details can therefore be highlighted from the surrounding tissues. Triphasic CT enables the inspection of a wide range of liver tumors, and helps doctors identify tumor types. However, as the amount of data increases, the interpretation of CT images becomes challenging andtime-consuming. In this study, we proposed a medical image classifier (MIC) with a priori clustering method using affinity propagation algorithm. A set of three- and fo
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Books on the topic "Method backward propagation algorithm"

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Sangeetha, V., and S. Kevin Andrews. Introduction to Artificial Intelligence and Neural Networks. Magestic Technology Solutions (P) Ltd, Chennai, Tamil Nadu, India, 2023. http://dx.doi.org/10.47716/mts/978-93-92090-24-0.

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Artificial Intelligence (AI) has emerged as a defining force in the current era, shaping the contours of technology and deeply permeating our everyday lives. From autonomous vehicles to predictive analytics and personalized recommendations, AI continues to revolutionize various facets of human existence, progressively becoming the invisible hand guiding our decisions. Simultaneously, its growing influence necessitates the need for a nuanced understanding of AI, thereby providing the impetus for this book, “Introduction to Artificial Intelligence and Neural Networks.” This book aims to equip it
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Book chapters on the topic "Method backward propagation algorithm"

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Jaulin, Luc, Isabelle Braems, Michel Kieffer, and Éric Walter. "Nonlinear State Estimation Using Forward-Backward Propagation of Intervals in an Algorithm." In Scientific Computing, Validated Numerics, Interval Methods. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-6484-0_16.

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Zeng, Xiangming, and Liangqu Long. "Backward Propagation Algorithm." In Beginning Deep Learning with TensorFlow. Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-7915-1_7.

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Tan, Yong Kiam, Marijn J. H. Heule, and Magnus O. Myreen. "cake_lpr: Verified Propagation Redundancy Checking in CakeML." In Tools and Algorithms for the Construction and Analysis of Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72013-1_12.

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AbstractModern SAT solvers can emit independently checkable proof certificates to validate their results. The state-of-the-art proof system that allows for compact proof certificates is propagation redundancy (PR). However, the only existing method to validate proofs in this system with a formally verified tool requires a transformation to a weaker proof system, which can result in a significant blowup in the size of the proof and increased proof validation time. This paper describes the first approach to formally verify PR proofs on a succinct representation; we present (i) a new Linear PR (L
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Yoo, Jang-Hee, Jae-Woo Kim, and Jong-Uk Choi. "An Adaptive Training Method of Back-Propagation Algorithm." In Intelligent Systems Third Golden West International Conference. Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-7108-3_55.

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Sun, Wencheng, and Xiaoyong Chen. "Hierarchical Feature Selection Method Based on Sequential Backward Selection Algorithm for Fasting Blood Glucose Prediction." In Communications in Computer and Information Science. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-1490-5_12.

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Wang, Kunfu, Ruolin Xing, Wei Feng, and Baiqiao Huang. "A Method of UAV Formation Transformation Based on Reinforcement Learning Multi-agent." In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_20.

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AbstractIn the face of increasingly complex combat tasks and unpredictable combat environment, a single UAV can not meet the operational requirements, and UAVs perform tasks in a cooperative way. In this paper, an improved heuristic reinforcement learning algorithm is proposed to solve the formation transformation problem of multiple UAVs by using multi-agent reinforcement learning algorithm and heuristic function. With the help of heuristic back-propagation algorithm for formation transformation, the convergence efficiency of reinforcement learning is improved. Through the above reinforcement
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Takahashi, Satoshi, Kazuhito Ishida, Hiroshi Yoshiura, and Arata Nakagoshi. "An Evaluation Point Culling Algorithm for Radio Propagation Simulation based on the Imaging Method." In Wireless Personal Communications. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-5491-2_12.

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Liu, Weimin, Zhongzhi Hu, Jiqiang Wang, and Shengyi Liu. "A Self-tuning Controller Design Method Based on LQG/LTR and Back Propagation Algorithm." In Lecture Notes in Electrical Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9686-2_30.

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Takahashi, Satoshi, Kazuhito Ishida, Hiroshi Yoshiura, and Arata Nakagoshi. "An Evaluation Point Culling Algorithm for Radio Propagation Simulation based on the Imaging Method." In The Kluwer International Series in Engineering and Computer Science. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1331-1_12.

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Zhao, Mengyu, Shaowei Cai, and Yuhang Qian. "Distributed SMT Solving Based on Dynamic Variable-Level Partitioning." In Computer Aided Verification. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65627-9_4.

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AbstractSatisfiability Modulo Theories on arithmetic theories have significant applications in many important domains. Previous efforts have been mainly devoted to improving the techniques and heuristics in sequential SMT solvers. With the development of computing resources, a promising direction to boost performance is parallel and even distributed SMT solving. We explore this potential in a divide-and-conquer view and propose a novel dynamic parallel framework with variable-level partitioning. To the best of our knowledge, this is the first attempt to perform variable-level partitioning for
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Conference papers on the topic "Method backward propagation algorithm"

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Shi, Tian, Zhonghua Liang, Bowen Dong, and Jing Zhang. "Indoor Visible Light Positioning Based on Backward Propagation Neural Network and Improved Osprey Optimization Algorithm." In 2025 10th International Conference on Computer and Communication System (ICCCS). IEEE, 2025. https://doi.org/10.1109/icccs65393.2025.11069473.

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Yan, Zhehao, Xueliang Gu, Tong Zhai, Guangxin Li, Yunjie Qi, and Yipeng Lu. "A Back Propagation Algorithm-Driven Design Method of Cantilever Beam." In 2024 IEEE International Symposium on Radio-Frequency Integration Technology (RFIT). IEEE, 2024. https://doi.org/10.1109/rfit60557.2024.10812513.

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Yang, Yi-Han, and Yong-Gang Zhou. "A Plane Wave Synthesis Method Based on Genetic Algorithm." In 2024 14th International Symposium on Antennas, Propagation and EM Theory (ISAPE). IEEE, 2024. https://doi.org/10.1109/isape62431.2024.10840405.

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Huang, Yuhang, Jingpeng Gao, Guilin Yu, and Tianran Zhang. "A Jamming Decision Method Based on SEEA-TD3 Algorithm." In 2024 IEEE 12th Asia-Pacific Conference on Antennas and Propagation (APCAP). IEEE, 2024. https://doi.org/10.1109/apcap62011.2024.10881916.

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Wang, Zhengzhuo, Yanliang Sha, Lingyun Ouyang, Quan Chen, and Jianguo Hu. "A Fast Parallel Algorithm Based on GPU for Harmonic Balance Method." In 2024 IEEE 12th Asia-Pacific Conference on Antennas and Propagation (APCAP). IEEE, 2024. https://doi.org/10.1109/apcap62011.2024.10881553.

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Cao, Yiyan, Xuanmin Wang, Lina Ma, Yuchen Li, and Changzhan Gu. "Multi-target Tracking Algorithm Based on Super-precision Distance Estimation Method." In 2024 IEEE 12th Asia-Pacific Conference on Antennas and Propagation (APCAP). IEEE, 2024. https://doi.org/10.1109/apcap62011.2024.10881232.

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Guo, Guangbin, Rongshen Zhan, Lixin Guo, and Rui Wang. "A Range-Doppler Map Simulation Method Based on Near-Field Electromagnetic Scattering Algorithm." In 2024 14th International Symposium on Antennas, Propagation and EM Theory (ISAPE). IEEE, 2024. https://doi.org/10.1109/isape62431.2024.10841296.

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Li, Gang, Haijun He, Bo Tian, Pengfei Hu, Tiantian Feng, and Yuanfei Hui. "Ground Target Recognition Method for Laser Proximity Fuze Echo Based on KNN Algorithm." In 2024 14th International Symposium on Antennas, Propagation and EM Theory (ISAPE). IEEE, 2024. https://doi.org/10.1109/isape62431.2024.10840907.

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Lin, Hong Huey, and Adrian Korpel. "Novel beam propagation method taking into account continuous reflections." In OSA Annual Meeting. Optica Publishing Group, 1989. http://dx.doi.org/10.1364/oam.1989.thg2.

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The beam propagation method, also known as the split-step or marching algorithm, is well known for its application to the simulation of wave propagation in inhomogeneous or cubically nonlinear (Kerr) media. In essence it treats the propagation medium as a sequence of thin phase filters (self-induced in the nonlinear case) separated by thin regions of homogeneous space.1 Reflections due to gradients of the refractive index in the nominal propagation direction are ignored. One recent variant of the technique,2 used for optical waveguide investigations, takes into account multiple discrete reflec
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Bakir, O., O. A. Civi, V. B. Erturk, and Hsi-Tseng Chou. "Fast Analysis of Large Microstrip Patch Phased Arrays Using Generalized Forward Backward Method with DFT Based Acceleration Algorithm." In 2006 IEEE Antennas and Propagation Society International Symposium. IEEE, 2006. http://dx.doi.org/10.1109/aps.2006.1711513.

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Reports on the topic "Method backward propagation algorithm"

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Morkun, Vladimir S., Natalia V. Morkun, and Andrey V. Pikilnyak. Augmented reality as a tool for visualization of ultrasound propagation in heterogeneous media based on the k-space method. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3757.

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For programming the AR tools, interactive objects and creating the markers, the method of fiber spaces (k-space) for modeling of ultrasonic wave propagation in an inhomogeneous medium using coarse grids, with maintaining the required accuracy was used. The algorithm and tools of augmented reality were introduced into the adaptive control system of the pulp gas phase in the iron ore flotation process using a control action on the basis of high-energy ultrasound dynamic effects generated by ultrasonic phased arrays. The tools of augmented reality based on k-space methods allow to facilitate wide
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti
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