Journal articles: 'Adaptive equalizations'

1

Qureshi, S. U. H. "Adaptive equalization." Proceedings of the IEEE 73, no. 9 (1985): 1349–87. http://dx.doi.org/10.1109/proc.1985.13298.

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Chen, Wei, Kohei Inoue, and Kenji Hara. "Adaptive Aggregated Histogram Equalization for Color Image Enhancement without Gamut Problem." Journal of the Institute of Industrial Applications Engineers 8, no. 2 (April 25, 2020): 56–62. http://dx.doi.org/10.12792/jiiae.8.56.

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Diana D.C, Diana D. C., Joy Vasantha Rani S. P. Joy Vasantha Rani.S.P, Nithya T. R. Nithya.T.R, and Srimukhee B. Srimukhee.B. "Adaptive Inertia Weight Particle Swarm Optimization For Linear and Nonlinear Channel Equalization." International Journal of Scientific Research 3, no. 4 (June 1, 2012): 1–4. http://dx.doi.org/10.15373/22778179/apr2014/181.

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Bergmans, Jan W. M., Maria Yu Lin, David Modrie, and Rob Otte. "Asynchronous LMS adaptive equalization." Signal Processing 85, no. 7 (July 2005): 1301–13. http://dx.doi.org/10.1016/j.sigpro.2004.12.006.

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Lim, Seung-Gag. "Performance Improvement of MCMA Equalization Algorithm Using Adaptive Modulus." Journal of the Institute of Webcasting, Internet and Telecommunication 14, no. 3 (June 30, 2014): 57–62. http://dx.doi.org/10.7236/jiibc.2014.14.3.57.

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Lim, Seung-Gag. "Performance Evaluation of H-MMA Adaptive Equalization Algorithm using Adaptive Modulus and Adaptive Step Size." Journal of the Institute of Internet Broadcasting and Communication 17, no. 1 (February 28, 2017): 83–88. http://dx.doi.org/10.7236/jiibc.2017.17.1.83.

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Sun, Lin, Ming Yan, Haisen Li, and Yanjie Xu. "Joint Time-Reversal Space-Time Block Coding and Adaptive Equalization for Filtered Multitone Underwater Acoustic Communications." Sensors 20, no. 2 (January 9, 2020): 379. http://dx.doi.org/10.3390/s20020379.

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Underwater acoustic (UWA) sensor networks demand high-rate communications with high reliability between sensor nodes for massive data transmission. Filtered multitone (FMT) is an attractive multicarrier technique used in high-rate UWA communications, and can obviously shorten the span of intersymbol interference (ISI) with high spectral efficiency and low frequency offset sensitivity by dividing the communication band into several separated wide sub-bands without guard bands. The joint receive diversity and adaptive equalization scheme is often used as a general ISI suppression technique in FMT-UWA communications, but large receive array for high diversity gain has an adverse effect on the miniaturization of UWA sensor nodes. A time-reversal space-time block coding (TR-STBC) technique specially designed for frequency-selective fading channels can replace receive diversity with transmit diversity for high diversity gain, and therefore is helpful for ISI suppression with simple receive configuration. Moreover, the spatio-temporal matched filtering (MF) in TR-STBC decoding can mitigate ISI obviously, and therefore is of benefit to lessen the complexion of adaptive equalization for post-processing. In this paper, joint TR-STBC and adaptive equalization FMT-UWA communication method is proposed based on the merit of TR-STBC. The proposed method is analyzed in theory, and its performance is assessed using simulation analysis and real experimental data collected from an indoor pool communication trial. The validity of the proposed method is proved through comparing the proposed method with the joint single-input–single-output (SISO) and adaptive equalization method and the joint single-input–multiple-output (SIMO) and adaptive equalization method. The results show that the proposed method can achieve better communication performance than the joint SISO and adaptive equalization method, and can achieve similar performance with more simpler receive configuration as the joint SIMO and adaptive equalization method.

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Peng, Na Xin, and Yu Qiang Chen. "Improved Self-Adaptive Image Histogram Equalization Algorithm." Advanced Materials Research 760-762 (September 2013): 1495–500. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.1495.

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Histogram equalization (HE) algorithm is wildly used method in image processing of contrast adjustment using images histogram. This method is useful in images with backgrounds and foreground that are both bright or both dark. But the performance of HE is not satisfactory to images with backgrounds and foregrounds that are both bright or both dark. To deal with the above problem, [ gives an improved histogram equalization algorithm named self-adaptive image histogram equalization (SIHE) algorithm. Its main idea is to extend the gray level of the image which firstly be processed by the classical histogram equalization algorithm. This paper gives detailed introduction to SIHE and analyzes the shortage of it, then give an improved version of SIHE named ISIHE, finally do experiments to show the performance of our algorithm.

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Guo, Ye Cai, and Kang Fan. "Blind Equalization Algorithm Based on Adaptive Genetic Algorithm and Wavelet Transform." Applied Mechanics and Materials 44-47 (December 2010): 3215–19. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.3215.

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Constant Modulus Algorithm(CMA) has slow convergence speed and easily immerges in local minimum owing to lack of initialization theory. Aiming at these disadvantages, adaptive genetic parameters are introduced into constant modulus blind equalization algorithm based on Genetic Algorithm and Wavelet Transform(GAWT-CMA), and Constant Modulus blind equali- zation Algorithm based on Adaptive Genetic Algorithm and Wavelet Transform(AGAWT-CMA) was proposed. The proposed algorithm processes genetic parameters adaptively, which can not only save the excellence individual with large probability but also avoid stagnancy during the evolution process. So it is propitious to search the whole optimum solution in overall range. The performance of the proposed algorithm was verified by computer simulation with underwater acoustic channels.

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Sun, Lin, Mei Wang, Guoheng Zhang, Haisen Li, and Lan Huang. "Filtered Multitone Modulation Underwater Acoustic Communications Using Low-Complexity Channel-Estimation-Based MMSE Turbo Equalization." Sensors 19, no. 12 (June 17, 2019): 2714. http://dx.doi.org/10.3390/s19122714.

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Filtered multitone (FMT) modulation divides the communication band into several subbands to shorten the span of symbols affected by multipath in underwater acoustic (UWA) communications. However, there is still intersymbol interference (ISI) in each subband of FMT modulation degrading communication performance. Therefore, ISI suppression techniques must be applied to FMT modulation UWA communications. The suppression performance of traditional adaptive equalization methods often exploited in FMT modulation UWA communications is limited when the effect of ISI spans tens of symbols or large constellation sizes are used. Turbo equalization consisting of adaptive equalization and channel decoding can improve equalization performance through information exchanging and iterative processes. To overcome the shortcoming of traditional minimum mean square error (MMSE) equalization and effectively suppress the ISI with relatively low computation complexity, an FMT modulation UWA communication using low-complexity channel-estimation-based (CE-based) MMSE turbo equalization is proposed in this paper. In the proposed method, turbo equalization is first exploited to suppress the ISI in FMT modulation UWA communications, and the equalizer coefficients of turbo equalization are adjusted using the low-complexity CE-based MMSE algorithm. The proposed method is analyzed in theory and verified by simulation analysis and real data collected in the experiment carried out in a pool with multipath propagation. The results demonstrate that the proposed method can achieve better communication performance with a higher bit rate than the FMT modulation UWA communication using traditional MMSE adaptive equalization.

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Wijaya Kusuma, I. Wayan Angga, and Afriliana Kusumadewi. "PENERAPAN METODE CONTRAST STRETCHING, HISTOGRAM EQUALIZATION DAN ADAPTIVE HISTOGRAM EQUALIZATION UNTUK MENINGKATKAN KUALITAS CITRA MEDIS MRI." Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer 11, no. 1 (April 30, 2020): 1–10. http://dx.doi.org/10.24176/simet.v11i1.3153.

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Citra medis adalah suatu pola atau gambar dua dimensi bagian dalam tubuh manusia yang digunakan oleh ahli kesehatan untuk mendeteksi dan menganalisa penyakit pasien. Pada bidang radiologi citra yang sering digunakan saat ini adalah citra Magnetic resonance Imaging (MRI). Keunggulan citra MRI adalah kemampuan menampilkan detail anatomi secara jelas dalam berbagai potongan (multiplanar) tanpa mengubah posisi pasien. Citra MRI ini akan digunakan oleh dokter ataupun peneliti untuk melakukan analisis ada tidaknya suatu tumor, kanker, atau kelainan pada pasien. Penelitian ini mengusulkan metode Contrast Stretching, Histogram Equalization dan Adaptive Histogram Equalization untuk meningkatkan kualitas citra medis. Batasan masalah penelitian ini adalah citra medis MRI yang digunakan sebagai obyek penelitian adalah citra medis MRI Otak baik yang normal atau yang mengalami lesi (gangguan). Dari hasil kualitas citra dan analisa kuantitatif menunjukkan bahwa metode contrast stretching menghasilkan hasil kualitas citra MRI jauh lebih baik dibandingkan dengan metosde histogram equalization, dan adaptive histogram equalization. Nilai MSE yang paling rendah adalah pada metode contrast stretching yaitu 0,00346. Sedangkan nilai MSE yang paling besar dihasilkan oleh metode histogram equalization. Kualitas citra dengan metode contrast stretching menghasilkan nilai PSNR yang paling besar yaitu 22,0677. Ini menandakan bahwa kualitas citra dari metode contrast stretching jauh lebih baik dibandingkan metode histogram equalization, dan adaptive histogram equalization.

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Laot, C., A. Glavieux, and J. Labat. "Turbo equalization: adaptive equalization and channel decoding jointly optimized." IEEE Journal on Selected Areas in Communications 19, no. 9 (2001): 1744–52. http://dx.doi.org/10.1109/49.947038.

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D.C., Diana, and Joy Vasantha Rani S.P. "Novel cat swarm optimization algorithm to enhance channel equalization." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 36, no. 1 (January 3, 2017): 350–63. http://dx.doi.org/10.1108/compel-08-2015-0289.

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Purpose Adaptive equalization plays an important role in digital communication to reduce the distortions due to inter-symbol interference. An adaptive filter is used as an equalizer model in channel equalization. An adaptive algorithm is the heart of the adaptive filter which finds the optimum coefficients of the filter. The choice of the adaptive algorithm improves the convergence rate and minimizes the mean square error (MSE). This paper aims to propose a cat swarm optimization (CSO)-based adaptive algorithm and its modification to improve the performance of a channel equalizer. Design/methodology/approach The input digital training data are transmitted through different channel conditions. A linear transversal filter is used as a channel and equalizer model. The equalizer coefficients are trained by the proposed simplified cat swarm optimization (SCSO) algorithm to find the estimated digital training data. Findings The performance of the proposed SCSO algorithm is compared with particle swarm optimization (PSO)-based channel equalization. The improvement in convergence rate and MSE is verified under linear and nonlinear channel conditions with different delay spreads. The optimum parameters of the SCSO are found using simulation-based sensitivity analysis. Originality/value This paper analyzes a CSO algorithm for adaptive channel equalization and proposes a SCSO algorithm to identify the optimum coefficients of a transversal equalizer. The seeking mode process is simplified in the proposed SCSO to achieve better performance in channel equalization. The proposed SCSO algorithm guarantees minimum MSE in all independent runs, whereas in PSO, few misses are possible.

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Wang, Wen Bin, Dao Yuan Liu, and Yu Qin Yao. "Research of Equalization Technology Based on Matlab." Applied Mechanics and Materials 513-517 (February 2014): 3786–89. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3786.

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In the modern digital communication system, inter-symbol interference (ISI) caused by the imperfectness of the channel is a major factor that degrades the performance of communication. In order to decrease the influence of ISI and improve communication quality, people usually use equalization technology. Generally, channel response is changing over time, so the adaptive equalizer is necessary. This paper firstly introduced the theoretical foundation and realization method of the adaptive equalization system. Then discuss the LMS algorithm. Finally, the SIMULINK tool is used to build a communication system. The set of simulation results by observing the eye diagrams of the signals before and after equalization have validated the equalization effect.

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15

Abrar, Shafayat, and Asoke K. Nandi. "Adaptive Minimum Entropy Equalization Algorithm." IEEE Communications Letters 14, no. 10 (October 2010): 966–68. http://dx.doi.org/10.1109/lcomm.2010.083110.101168.

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16

Swindlehurst, A. L. "Normalized adaptive decision directed equalization." IEEE Signal Processing Letters 5, no. 1 (January 1998): 18–20. http://dx.doi.org/10.1109/97.654869.

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Bergmans, Jan W. M., Haris Pozidis, and Maria Yu Lin. "Asynchronous zero-forcing adaptive equalization." European Transactions on Telecommunications 16, no. 6 (2005): 545–56. http://dx.doi.org/10.1002/ett.1001.

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Peloso, R. A. "Adaptive equalization for advanced television." IEEE Transactions on Consumer Electronics 38, no. 3 (1992): 119–26. http://dx.doi.org/10.1109/30.156672.

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Bergmans, J. W. M., and M. Y. Lin. "Leaky Zero-Forcing Adaptive Equalization." IEEE Signal Processing Letters 11, no. 2 (February 2004): 129–31. http://dx.doi.org/10.1109/lsp.2003.819878.

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Stark, J. A., and W. J. Fitzgerald. "Model-based adaptive histogram equalization." Signal Processing 39, no. 1-2 (September 1994): 193–200. http://dx.doi.org/10.1016/0165-1684(94)90133-3.

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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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Zheng, Xiao Tian, Ji Lin Li, Yun Jie Zhang, Mo Lin, Xing Rong Wang, Jian Wang, Xiu Mao, and Xin Hua Li. "A Fast and Robust Adaptive Blind Equalization Algorithm in High Speed Satellite Channel." Applied Mechanics and Materials 333-335 (July 2013): 1435–41. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.1435.

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In this paper, a novel combined leakage CMA and direct decision (DD) adaptive algorithm using automatic iteration step adaptive blind equalizer is presented. In contrast to known CMA algorithm, the novel algorithm can approach the performance of mean-square error and fast convergent rate. For adaption of filters, efficient automatic iteration step and DD algorithm is present. The novel algorithm is lower computational complexity withO(N) and N is the filter order. Furthermore, the relation of novel algorithm to CMA algorithm is investigated. Finally, it is shown that proposed combined LCMA-DD algorithm is robust against amplitude and phase offset with fast convergence and mean-square error.

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Golani, Ori, Meir Feder, and Mark Shtaif. "Equalization Methods for Out-of-Band Nonlinearity Mitigation in Fiber-Optic Communications." Applied Sciences 9, no. 3 (February 2, 2019): 511. http://dx.doi.org/10.3390/app9030511.

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In recent years, it has been established that the adverse effects of nonlinear interference noise (NLIN) can be mitigated using adaptive equalization methods. As such, a wide variety of adaptive equalization methods have been used to treat nonlinearity, in different transmission scenarios. This paper reviews the principles of out-of-band nonlinearity mitigation using adaptive equalization. Statistical properties of NLIN that can be exploited for mitigation are discussed, as well as the cost and benefit of various types of equalizers. In particular we describe the equivalence between the NLIN and time-dependent inter-symbol-interference (ISI) and discuss ways in which the ISI coefficients can be characterized theoretically and experimentally. We further discuss the effectiveness of existing ISI mitigation algorithms, and explain the need for designing customized algorithms that take advantage of the various correlation properties characterizing the ISI coefficients. This paper is intended to be a practical reference for researchers who want to apply equalization algorithms or design new methods for nonlinearity mitigation.

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Cai, Chen, Jian-zhong Zhao, and Yu-mei Zhou. "A 1.25–12.5 Gbps Adaptive CTLE with Asynchronous Statistic Eye-Opening Monitor." Journal of Electrical and Computer Engineering 2018 (November 15, 2018): 1–9. http://dx.doi.org/10.1155/2018/3095950.

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The equalization of a large attenuation signal and multirate communication in high-speed serial interface is hard to balance. To overcome this difficulty, an adaptive equalization system with optimized eye-opening monitor is proposed. The designed eye-opening monitor is based on the asynchronous statistic eye diagram tracking algorithm, and the eye diagram is obtained by undersampling with the low-speed asynchronous clock. With the eye-opening monitor into the adaptive loop, an adaptive equalization system combined with continuous-time linear equalization (CTLE) is completed. And the inductor peaking technology is used to improve the capacity of compensation. With SMIC 28 nm CMOS process to achieve the overall design, the power consumption and core chip area are 12 mW @ 12.5 Gbps and 0.12 mm2, respectively. And postsimulation results show that it can offer compensation from 6 to 21 dB for 1.25–12.5 Gbps range of receiving data, which achieves a large range of data rate and channel loss, and its power efficiency is 0.046 pJ/bit/dB for the worst case, which is better than most previous works.

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Lawton, Sahil, and Serestina Viriri. "Detection of COVID-19 from CT Lung Scans Using Transfer Learning." Computational Intelligence and Neuroscience 2021 (April 8, 2021): 1–14. http://dx.doi.org/10.1155/2021/5527923.

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This paper aims to investigate the use of transfer learning architectures in the detection of COVID-19 from CT lung scans. The study evaluates the performances of various transfer learning architectures, as well as the effects of the standard Histogram Equalization and Contrast Limited Adaptive Histogram Equalization. The findings of this study suggest that transfer learning-based frameworks are an alternative to the contemporary methods used to detect the presence of the virus in patients. The highest performing model, the VGG-19 implemented with the Contrast Limited Adaptive Histogram Equalization, on a SARS-CoV-2 dataset, achieved an accuracy and recall of 95.75% and 97.13%, respectively.

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Ruqi Zhang, Ruqi Zhang, Jianfeng Li Jianfeng Li, Zhitong Huang Zhitong Huang, and Yuefeng Ji Yuefeng Ji. "Adaptive frequency domain pre-equalization for white-LED nonlinearity in OFDM-based visible light communication systems." Chinese Optics Letters 13, no. 7 (2015): 072302–72305. http://dx.doi.org/10.3788/col201513.072302.

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Rahaman,, Abu Sayed Md Mostafizur, Md Imdadul Islam, and M. R. Amin. "Application of Zero-Forcing Adaptive Equalization in Compensation of Fading Effect of Two-hop Wireless Link." International Journal of Engineering and Technology 3, no. 6 (2011): 628–31. http://dx.doi.org/10.7763/ijet.2011.v3.296.

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Riadi, Aditya Akbar, Ahmad Abdul Chamid, and Akh Sokhibi. "ANALISIS KOMPARASI METODE PERBAIKAN KONTRAS BERBASIS HISTOGRAM EQUALIZATION PADA CITRA MEDIS." Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer 8, no. 1 (April 1, 2017): 383–88. http://dx.doi.org/10.24176/simet.v8i1.1026.

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Citra merupakan gambaran tentang karakteristik suatu obyek menurut kondisi variabel tertentu. Pengolahan citra bertujuan memperbaiki kualitas citra agar mudah diinterpretasi oleh manusia atau mesin (dalam hal ini komputer). Terdapat beberapa operasi di dalam pengolahan citra, salah satunya adalah perbaikan kontras yang pada dasarnya biasa digunakan untuk memunculkan bagian-bagian yang tidak terlihat (hidden feature) pada citra. Hasil citra dari rontgen yang tidak selalu memiliki kualitas citra yang baik, seperti halnya hasil citra x-ray yang terlalu gelap atau ada bagian tulang yang terlihat samar sehingga gambar tidak terlihat jelas. Pada penelitian ini teknik peningkatan citra dengan perbaikan kontras menggunakan metode berbasis Histrogram Equalization. Pada citra medis tersebut dan juga menunjukkan kinerja hasil pengukuran kontrol eror menggunakan Mean Square Error menjelaskan bahwa metode Contrast Limited Adaptive Histogram Equalization lebih baik dibandingkan dengan metode Histrogram Equalization dan metode Adaptive Histogram Equalization.

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Raghavendra, M. M. "Adaptive Image Equalization for Contrast Enhancement." International Journal for Research in Applied Science and Engineering Technology V, no. III (March 28, 2017): 978–82. http://dx.doi.org/10.22214/ijraset.2017.3180.

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Patra, Sarat Kumar, and Bernard Mulgrew. "Fuzzy techniques for adaptive nonlinear equalization." Signal Processing 80, no. 6 (June 2000): 985–1000. http://dx.doi.org/10.1016/s0165-1684(00)00015-3.

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Prelcic, Nuria González, Fernando Pérez González, and M. Elena Domı́nguez Jiménez. "Wavelet packet-based subband adaptive equalization." Signal Processing 81, no. 8 (August 2001): 1641–62. http://dx.doi.org/10.1016/s0165-1684(01)00077-9.

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Gelfand, S. B., C. Ravishankar, and E. J. Delp. "Tree-structured piecewise linear adaptive equalization." IEEE Transactions on Communications 41, no. 1 (1993): 70–82. http://dx.doi.org/10.1109/26.212367.

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Yellepeddi, Atulya, and James C. Preisig. "Adaptive Equalization in a Turbo Loop." IEEE Transactions on Wireless Communications 14, no. 9 (September 2015): 5111–22. http://dx.doi.org/10.1109/twc.2015.2432764.

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Eleftheriou, E., and D. Falconer. "Adaptive Equalization Techniques for HF Channels." IEEE Journal on Selected Areas in Communications 5, no. 2 (February 1987): 238–47. http://dx.doi.org/10.1109/jsac.1987.1146531.

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Pizer, Stephen M., E. Philip Amburn, John D. Austin, Robert Cromartie, Ari Geselowitz, Trey Greer, Bart ter Haar Romeny, John B. Zimmerman, and Karel Zuiderveld. "Adaptive histogram equalization and its variations." Computer Vision, Graphics, and Image Processing 39, no. 3 (September 1987): 355–68. http://dx.doi.org/10.1016/s0734-189x(87)80186-x.

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Stimper, Vincent, Stefan Bauer, Ralph Ernstorfer, Bernhard Scholkopf, and Rui Patrick Xian. "Multidimensional Contrast Limited Adaptive Histogram Equalization." IEEE Access 7 (2019): 165437–47. http://dx.doi.org/10.1109/access.2019.2952899.

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Gerstacker, W. H., R. R. Muller, and J. B. Huber. "Iterative equalization with adaptive soft feedback." IEEE Transactions on Communications 48, no. 9 (2000): 1462–66. http://dx.doi.org/10.1109/26.870012.

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Zhang, Q. "Adaptive equalization using the backpropagation algorithm." IEEE Transactions on Circuits and Systems 37, no. 6 (June 1990): 848–49. http://dx.doi.org/10.1109/31.55048.

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Venkatadri, Arvind, and Jai Krishna Gautam. "Study of Algorithms for Adaptive Equalization." IETE Technical Review 5, no. 1 (January 1988): 19–25. http://dx.doi.org/10.1080/02564602.1988.11438212.

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Li, Lu, Xinyu Fan, Haimei Gong, Yuanqi Wang, and Lei Wang. "Intelligent Equalization Based on RBF LSSVM and Adaptive Channel Decoding in Faster-than-Nyquist Receiver." International Journal of Pattern Recognition and Artificial Intelligence 35, no. 09 (April 8, 2021): 2158005. http://dx.doi.org/10.1142/s0218001421580052.

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On one hand, aiming at the prominent problem of improving the reliability of Faster-than-Nyquist (FTN) wireless transmission, abandoning the channel estimation, we propose the Radial Basis Function Least Squares Support Vector Machine (RBF LSSVM) algorithm based on Intelligent Signal Processing for FTN equalization and form FTN time domain transverse filter equalizer. The model of FTN wireless communication system based on equalization of LSSVM algorithm is established by adding 50-bit training sample sequence module. On the other hand, in the FTN transmission BPSK modulation system receiving terminal, we propose joint research equalization of LSSVM algorithm and adaptive channel decoding scheme of Chase algorithm, to improve the reliable transmission performance of FTN wireless communication. The threshold value is 20, and the adaptive 2-D Turbo Product Codes (TPC) encoding and decoding is simulated by four iterations. The BER performance of FTN wireless communication combined with LSSVM algorithm and TPC adaptive decoding is simulated.

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Yang, Zhuangchun, Tianyi Liang, Zhourong Deng, and Youwen Zhang. "Improved proportionate FONLMS algorithm based direct adaptive Turbo equalization for MIMO underwater acoustic communications." MATEC Web of Conferences 283 (2019): 07003. http://dx.doi.org/10.1051/matecconf/201928307003.

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In this paper, a novel normalized least mean squares (NLMS) algorithm that jointly updates the efficient of the linear equalizer and soft interference canceller (SIC) in an adaptive turbo equalizer for multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications. To exploit the sparsity of MIMO UWA channels and enhance the convergence speed of adaptive equalization, improved proportionate fast self-optimized NLMS algorithm (IPFONLMS), is proposed to well adapt to sparse channel with the similar complexity as improve proportionate NLMS (IPNLMS) algorithm. Then we extend the proposed algorithm to the adaptive turbo equalization for MIMO UWA communications. The performance of the proposed adaptive algorithm is evaluated by numerical results. Simulation results show that the improved data efficiency and bit error ratio (BER) performance of the proposed receiver is achieved over adaptive turbo equalizer based on the IPNLMS algorithm.

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Shouyu, Sun. "Blind Adaptive Channel Equalization Using Modified CMA." Advanced Materials Research 658 (January 2013): 537–40. http://dx.doi.org/10.4028/www.scientific.net/amr.658.537.

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The constant modulus algorithm (CMA) equalizer is perhaps the best known and the most popular scheme for blind adaptive channel equalization. In this paper, a modified constant modulus algorithm (modified CMA or MCMA) is proposed by modifying its error function. We have discussed the MCMA to blind channel equalization for baud-rat sampling in single-user case. Computer simulations are provided for 8PSK signals in noise environments under frequency selective channels. Results demonstrate that the MCMA displays much superior performance to the CMA for both convergence-time and intersymbol interference (ISI) or mean square error (MSE).

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Abood, Loay Kadom. "Contrast enhancement of infrared images using Adaptive Histogram Equalization (AHE) with Contrast Limited Adaptive Histogram Equalization (CLAHE)." Iraqi Journal of Physics (IJP) 16, no. 37 (September 11, 2018): 127–35. http://dx.doi.org/10.30723/ijp.v16i37.84.

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The objective of this paper is to improve the general quality of infrared images by proposes an algorithm relying upon strategy for infrared images (IR) enhancement. This algorithm was based on two methods: adaptive histogram equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The contribution of this paper is on how well contrast enhancement improvement procedures proposed for infrared images, and to propose a strategy that may be most appropriate for consolidation into commercial infrared imaging applications.The database for this paper consists of night vision infrared images were taken by Zenmuse camera (FLIR Systems, Inc) attached on MATRIC100 drone in Karbala city. The experimental tests showed significant improvements.

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Zhuang, Liyun, and Yepeng Guan. "Adaptive Image Enhancement Using Entropy-Based Subhistogram Equalization." Computational Intelligence and Neuroscience 2018 (August 13, 2018): 1–13. http://dx.doi.org/10.1155/2018/3837275.

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A novel image enhancement approach called entropy-based adaptive subhistogram equalization (EASHE) is put forward in this paper. The proposed algorithm divides the histogram of input image into four segments based on the entropy value of the histogram, and the dynamic range of each subhistogram is adjusted. A novel algorithm to adjust the probability density function of the gray level is proposed, which can adaptively control the degree of image enhancement. Furthermore, the final contrast-enhanced image is obtained by equalizing each subhistogram independently. The proposed algorithm is compared with some state-of-the-art HE-based algorithms. The quantitative results for a public image database named CVG-UGR-Database are statistically analyzed. The quantitative and visual assessments show that the proposed algorithm outperforms most of the existing contrast-enhancement algorithms. The proposed method can make the contrast of image more effectively enhanced as well as the mean brightness and details well preserved.

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Xiao, Ying, and Zhen Xing Li. "Adaptive Blind Equalization with Variable Step-Size Modified by Attenuation Function." Key Engineering Materials 474-476 (April 2011): 1792–96. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.1792.

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Step-size is one of the important parameters which influence the performance of blind equalization, a variable step-size method control by attenuation function according to instantaneous gradient and iterative times is proposed in this paper. Initially, set larger step-size to obtain faster convergence, with iterative times increasing, step-size would decrease control by attenuation function for instantaneous gradient reducing. Step-size changes according to this method consistent with the demand variable step-size adaptive algorithm that can obtain combination of convergence rate and convergence precision to improve the performance of blind equalization. Simulations show that this method performs better than conventional blind equalization with constant step-size.

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Wang, Dan, and Chi Yun Xu. "Research on Adaptive Modulation and Coding Technology in LTE-A System." Applied Mechanics and Materials 513-517 (February 2014): 2534–37. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.2534.

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In order to further improve the throughput and performance of the LTE system in the LTE-A system,this paper proposes a kind of AMC before the channel equalization in the LTE-A system. The scheme will be the channel matrix rank, channel correlation and channel equalization of SNR together as parameter for MCS, through the CQI-SNR curve to find the channel equalization before the final CQI to complete the feedback.And it solves the problems that the traditional AMC only relies on the SNR, and the SNR accuracy requirements. The theory and simulation results show, this scheme can improve the system throughput and performance.

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Elmostafa, ATIFY, Cherki Daoui, and Ahmed BOUMEZZOUGH. "A Blind Identification and Equalization for MC-CDMA Transmission Channel using a New of Adaptive Filter Algorithm." Indonesian Journal of Electrical Engineering and Computer Science 5, no. 2 (February 1, 2017): 352. http://dx.doi.org/10.11591/ijeecs.v5.i2.pp352-362.

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A review of literature shows that there are a variety of adaptive filters. In this research study, we propose a new type of adaptive filter that increases the diversification used to compensate the channel distortion effect in the MC-CDMA transmission. First, we show expressions of the impulse responses of the filter in the case of a perfect channel. The adaptive filter was simulated was experienced by blind equalization for different cases of Gaussian white noise in the case of an MC-CDMA transmission with orthogonal frequency baseband for mobile radio downlink channel Bran A. Simulation Results of the proposed model shows the performance of the identification and blind equalization algorithm for MC-CDMA transmission chain using IFFT.

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Nurhidayah, Bannu Abdul Samad, and Bualkar Abdullah. "Perbandingan Metode Contrast Enhancement pada Citra CT-Scan Kanker Paru-paru." Gravitasi 19, no. 2 (December 31, 2020): 24–28. http://dx.doi.org/10.22487/gravitasi.v19i2.15360.

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Abstrak: Di Indonesia kanker paru menjadi penyebab kematian kedua setelah kanker payudara. Angka mortalitas yang cukup tinggi, maka penentuan diagnosis lebih awal memegang peranan yang sangat penting dalam manajemen terapi. Kelemahan CT-Scan dalam mendiagnosa kanker paru-paru disebabkan oleh kontras citra yang rendah dan derau pada citra. Pada penelitian ini akan membandingkan metode contrast enhancement berbasis histogram equalization dan contrast limited adaptive histogram equalization untuk meningkatkan kualitas citra dengan menggunakan software Matlab. Namun, sebelumnya dilakukan reduksi noise dengan menggunakan metode median filter. Kinerja dari setiap metode dihitung dengan mencari nilai MSE (Mean Square Error) dan PSNR (Peak Signal to Noise Ratio) citra. Dari nilai MSE dan PSNR yang di dapatkan diperoleh nilai MSE dan PSNR terbaik pada metode contrast limited adaptive histogram equalization dengan nilai 653,434 dB dan 245,547 dB.

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BASSIOUNY, M. "USING OF AN ADAPTIVE MATCHED FILTER IN SELF ADAPTIVE EQUALIZATION." International Conference on Aerospace Sciences and Aviation Technology 12, ASAT CONFERENCE (May 1, 2007): 1–7. http://dx.doi.org/10.21608/asat.2007.24368.

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Lim, Seung-Gag. "Performance Improvement of SMMA Adaptive Equalization Algorithm using Adaptive Modulus in QAM Signal." Journal of the Institute of Internet Broadcasting and Communication 16, no. 1 (February 29, 2016): 115–20. http://dx.doi.org/10.7236/jiibc.2016.16.1.115.

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Journal articles on the topic 'Adaptive equalizations'

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