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Journal articles on the topic 'Adaptive equalizer'

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Published: 4 June 2021

Last updated: 14 March 2023

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1

Simerjeet Kaur, Dr Kamal Kumar Sharma, and Mr. Navnidhi Sharma. "Analysis of BER Improvement of Adaptive Equalizer using CE and STB code." International Journal of Research in Informative Science Application & Techniques (IJRISAT) 3, no. 6 (June 25, 2019): 44–50. http://dx.doi.org/10.46828/ijrisat.v3i6.132.

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In a wireless communication channel, when the modulation bandwidth is exceeding the coherence bandwidth ISI takes place as the transmitted pulses are spread into the adjacent symbols. To combat the effects of ISI and noise and to reconstruct the signal and minimize Bit Error Rate (BER), the adaptive channel equalizer is used at the receiver end. Various kinds of interferences in a communication channel exists like Inter symbol Interference, Multipath Interference and Additive Interference which deals with the design of an Adaptive Equalizer. The idea of the equalizer is to build filter in the receiver that counter acts the effect of the channel. In essence, the equalizer must “unscatter” the impulse response and can be stated as the goal of designing the equalizer E so that the impulse response of the combined channel and equalizer CE has a single spike. We investigate channel equalization and introduce hierarchical and adaptive nonlinear channel equalization algorithms that are highly efficient and provide significantly enhanced bit error rate (BER) performance. Due to the high complexity of nonlinear equalizers and poor performance of linear ones, to equalize highly difficult channels, we employ piecewise linear equalizers.

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2

Pinchas, Monika. "Convolutional Noise PDF at the Convergence State of a Blind Adaptive Equalizer." MATEC Web of Conferences 210 (2018): 05003. http://dx.doi.org/10.1051/matecconf/201821005003.

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In the literature, the convolutional noise obtained at the output of a blind adaptive equalizer, is often modeled as a Gaussian process during the latter stages of the deconvolution process where the process is close to optimality. However, up to now, no strong mathematical basis was given supporting this phenomenon. Furthermore, no closed-form or closed-form approximated expression is given that shows what are the constraints on the system’s parameters (equalizer’s tap-length, input signal statistics, channel power, chosen equalization method and step-size parameter) for which the assumption of a Gaussian model for the convolutional noise holds. In this paper, we consider the two independent quadrature carrier input case and type of blind adaptive equalizers where the error that is fed into the adaptive mechanism which updates the equalizer’s taps can be expressed as a polynomial function of the equalized output up to order three. We show based on strong mathematical basis that the convolutional noise pdf at the latter stages of the deconvolution process where the process is close to optimality, is approximately Gaussian if complying on some constraints depending on the step-size parameter, input constellation statistics, channel power, chosen equalization method and equalizer’s tap-length. Simulation results confirm our findings.

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3

Sirithummachak, P., and C. Benjangkaprasert. "Adaptive Equalizer for DS-CDMA Multi-User Communication System Using Sign-Algorithm Based on Laguerre Filter Structure." Applied Mechanics and Materials 548-549 (April 2014): 1231–34. http://dx.doi.org/10.4028/www.scientific.net/amm.548-549.1231.

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This paper proposes a sign-algorithm based on adaptive Laguerre filter structure for improving the performance of the direct sequence-code division multiple access (DS-CDMA) communication system. The proposed adaptive equalizer employs a combination of sign and least mean square (LMS) algorithms to minimizing the effect of inter-symbol interference (ISI) that arises due to multipath propagation, and the computational complexity of equalizer. The performance of proposed equalizer was compared with traditional equalizers such as LMS and RLS algorithms in terms of varying path. The function detail and performance results of the proposed equalizer are described by computer simulations in terms of the bit error rate (BER).

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4

Bouguerra, Fateh, and Lamir Saidi. "An Eﬃcient ANN Interference Cancelation for High Order Modulation over Rayleigh Fading Channel." Journal of Telecommunications and Information Technology 8 (December 28, 2018): 75–80. http://dx.doi.org/10.26636/jtit.2018.125718.

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High order modulation (HOM) presents a key challenge in increasing spectrum eﬃciency in 4G and upcoming 5G communication systems. In this paper, two non-linear adaptive equalizer techniques based on multilayer perceptron (MLP) and radial basis function (RBF) are designed and applied on HOM to optimize its performance despite its high sensitivity to noise and channel distortions. The artiﬁcial neural network’s (ANN) adaptive equalizer architectures and learning methods are simpliﬁed to avoid more complexity and to ensure greater speed in symbol decision making. They will be compared with the following popular adaptive ﬁlters: least mean square (LMS) and recursive least squares (RLS), in terms of bit error rate (BER) and minimum square error (MSE) with 16, 64, 128, 256, 512 and 1024 quadrature amplitude modulation (QAM). By that, this work will show the advantage that the MLP equalizer has, in most cases, over RBF and traditional linear equalizers.

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5

Zerdoumi, Zohra, Djamel Chikouche, and Djamel Benatia. "Multilayer Perceptron Based Equalizer with an Improved Back Propagation Algorithm for Nonlinear Channels." International Journal of Mobile Computing and Multimedia Communications 7, no. 3 (July 2016): 16–31. http://dx.doi.org/10.4018/ijmcmc.2016070102.

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Neural network based equalizers can easily compensate channel impairments; such additive noise and inter symbol interference (ISI). The authors present a new approach to improve the training efficiency of the multilayer perceptron (MLP) based equalizer. Their improvement consists on modifying the back propagation (BP) algorithm, by adapting the activation function in addition to the other parameters of the MLP structure. The authors report on experiment results evaluating the performance of the proposed approach namely the back propagation with adaptive activation function (BPAAF) next to the BP algorithm. To further prove its effectiveness, the proposed approach is also compared beside a so known nonlinear equalizer explicitly the multilayer perceptron with decision feedback equalizer MLPDFE. The authors consider various performance measures specifically: signal resorted quality, lower steady state MSE reached and minimum bit error rate (BER) achieved, where nonlinear channel equalization problems are employed.

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6

Lucky, R. W. "The adaptive equalizer." IEEE Signal Processing Magazine 23, no. 3 (May 2006): 104–7. http://dx.doi.org/10.1109/msp.2006.1628883.

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7

Bhardwaj, Sumit, DR Vinod Shokeen, and Arun kumar. "A Review on Adaptive Equalizer Algorithms." International Journal of Scientific Research 3, no. 7 (June 1, 2012): 187–89. http://dx.doi.org/10.15373/22778179/july2014/59.

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8

Simerjeet Kaur, Dr Kamal Kumar Sharma, and Mr Navnidhi Sharma. "Literature Review on BER Improvement of Adaptive Equalizer." International Journal of Research in Informative Science Application & Techniques (IJRISAT) 3, no. 5 (May 15, 2019): 12–20. http://dx.doi.org/10.46828/ijrisat.v3i5.133.

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Channel equalization is an important aspect in high speed digital communication required for efficient and reliable data recovery and reception when the data is transmitted over band-limited channel subjected to noise and interference. We investigate channel equalization and introduce hierarchical and adaptive nonlinear channel equalization algorithms that are highly efficient and provide significantly improved bit error rate (BER) performance. Due to the high complexity of nonlinear equalizers and poor performance of linear ones, to equalize highly difficult channels, we employ piecewise linear equalizers.

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9

Wenqian, Huang, and Ding Wenrui. "Adaptive Equalizer Design for Unmanned Aircraft Vehicle Image Transmission over Relay Channels." Wireless Communications and Mobile Computing 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/5497926.

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A novel length adaptive method is proposed for time domain equalizer by taking the channel attenuation ratio between different multipath components into account in UAV-UAV and UAV-ground channels. Then, considering received image quality, the minimum bit error ratio (MBER) criterion is exploited to design adaptive equalizers for both amplify-and-forward (AF) and decode-and-forward (DF) relaying systems by the proposed length adaptive method. Results show that proposed MBER adaptive equalizers outperform the traditional ones in both AF relaying and DF relaying as channel attenuation ratio in UAV-ground channel increases. Moreover, DF outperforms AF as channel attenuation ratio in UAV-UAV channel increases. Furthermore, bit error ratio (BER) and peak signal-to-noise ratio (PSNR) performances in both AF and DF are evaluated to show the enhancement by the proposed MBER adaptive equalizers.

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10

ZERDOUMI, Zohra, Fadila BENMEDDOUR, Latifa ABDOU, and Djamel BENATIA. "An Adaptive Sigmoidal Activation Function for Training Feed Forward Neural Network Equalizer." Eurasia Proceedings of Science Technology Engineering and Mathematics 14 (December 31, 2021): 1–7. http://dx.doi.org/10.55549/epstem.1050144.

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Feed for word neural networks (FFNN) have attracted a great attention, in digital communication area. Especially they are investigated as nonlinear equalizers at the receiver, to mitigate channel distortions and additive noise. The major drawback of the FFNN is their extensive training. We present a new approach to enhance their training efficiency by adapting the activation function. Adapting procedure for activation function extensively increases the flexibility and the nonlinear approximation capability of FFNN. Consequently, the learning process presents better performances, offers more flexibility and enhances nonlinear capability of NN structure thus the final state kept away from undesired saturation regions. The effectiveness of the proposed method is demonstrated through different challenging channel models, it performs quite well for nonlinear channels which are severe and hard to equalize. The performance is measured throughout, convergence properties, minimum bit error achieved. The proposed algorithm was found to converge rapidly, and accomplish the minimum steady state value. All simulation shows that the proposed method improves significantly the training efficiency of FFNN based equalizer compared to the standard training one.

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11

Dong, Yabo, Hong Fan, Lin Ni, Zhaoli Shi, Ziwei Zhang, and Hong Fan. "Adaptive bit Modulation equalizer." Journal of Physics: Conference Series 1732 (January 2021): 012160. http://dx.doi.org/10.1088/1742-6596/1732/1/012160.

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12

Sobot, Robert. "Adaptive equalizer in CMOS." Canadian Journal of Electrical and Computer Engineering 32, no. 2 (2007): 83–86. http://dx.doi.org/10.1109/cjece.2007.365502.

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13

Kuo, S. M., and Yajie Yang. "Broadband adaptive noise equalizer." IEEE Signal Processing Letters 3, no. 8 (August 1996): 234–35. http://dx.doi.org/10.1109/97.511804.

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14

YUE, C. PATRICK, JAEJIN PARK, RUIFENG SUN, L. RICK CARLEY, and FRANK O'MAHONY. "LOW-POWER, PARALLEL INTERFACE WITH CONTINUOUS-TIME ADAPTIVE PASSIVE EQUALIZER AND CROSSTALK CANCELLATION." International Journal of High Speed Electronics and Systems 15, no. 02 (June 2005): 459–76. http://dx.doi.org/10.1142/s0129156405003260.

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This paper presents the low-power circuit techniques suitable for high-speed digital parallel interfaces each operating at over 10 Gbps. One potential application for such high-performance I/Os is the interface between the channel IC and the magnetic read head in future compact hard disk systems. First, a crosstalk cancellation technique using a novel data encoding scheme is introduced to suppress electromagnetic interference (EMI) generated by the adjacent parallel I/Os . This technique is implemented utilizing a novel 8-4-PAM signaling with a data look-ahead algorithm. The key circuit components in the high-speed interface transceiver including the receive sampler, the phase interpolator, and the transmitter output driver are described in detail. Designed in a 0.13-μm digital CMOS process, the transceiver consumes 310 mW per 10-Gps channel from a I-V supply based on simulation results. Next, a 20-Gbps continuous-time adaptive passive equalizer utilizing on-chip lumped RLC components is described. Passive equalizers offer the advantages of higher bandwidth and lower power consumption compared with conventional designs using active filter. A low-power, continuous-time servo loop is designed to automatically adjust the equalizer frequency response for the optimal gain compensation. The equalizer not only adapts to different channel characteristics, but also accommodates temperature and process variations. Implemented in a 0.25-μm, 1P6M BiCMOS process, the equalizer can compensate up to 20 dB of loss at 10 GHz while only consumes 32 mW from a 2.5-V supply.

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15

Khafaji, Mohammed J., and Maciej Krasicki. "Uni-Cycle Genetic Algorithm as an Adaptation Engine for Wireless Channel Equalizers." Electronics 11, no. 2 (January 6, 2022): 171. http://dx.doi.org/10.3390/electronics11020171.

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A recently developed adaptive channel equalizer driven by a so-called Uni-Cycle Genetic Algorithm (UCGA) is examined in the paper. The authors consider different initialization strategies of the iterative process and compare UCGA against the reference Recursive Least Squares (RLS) algorithm in terms of Bit Error Rate (BER) vs. Signal to Noise Ratio (SNR) performance and convergence rate of an adaptive channel equalizer. The results display a reasonable performance gain of UCGA over RLS for most of wireless channel models studied in the paper. Additionally, UCGA is capable of boosting the equalizer convergence. Thus, it can be considered a promising candidate for the future adaptive wireless channel equalizer.

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16

Kobo, Kazuo, Noriaki Morotomi, Yoichi Ishibashi, and Koji Oka. "Adaptive Equalizer for Teletext Receiver." IEEE Transactions on Consumer Electronics CE-32, no. 3 (August 1986): 533–37. http://dx.doi.org/10.1109/tce.1986.290075.

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17

Ali, Farman, Shabbir Ahmad, Fazal Muhammad, Ziaul Haq Abbas, Usman Habib, and Sunghwan Kim. "Adaptive Equalization for Dispersion Mitigation in Multi-Channel Optical Communication Networks." Electronics 8, no. 11 (November 17, 2019): 1364. http://dx.doi.org/10.3390/electronics8111364.

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Optical communication networks (OCNs) provide promising and cost-effective support for the ultra-fast broadband solutions, thus enabling them to address the ever growing demands of telecommunication industry such as high capacity and end users’ data rate. OCNs are used in both wired and wireless access networks as they offer many advantages over conventional copper wire transmission such as low power consumption, low cost, ultra-high bandwidth, and high transmission rates. Channel effects caused by light propagation through the fiber limits the performance, hence the data rate of the overall transmission. To achieve the maximum performance gain in terms of transmission rate through the OCN, an optical downlink system is investigated in this paper using feed forward equalizer (FFE) along with decision feedback equalizer (DFE). The simulation results show that the proposed technique plays a key role in dispersion mitigation in multi-channel optical transmission to uphold multi-Gb/s transmission. Moreover, bit error rate (BER) and quality factor (Q-factor) below 10 − 5 and above 5, respectively, are achieved with electrical domain equalizers for the OCN in the presence of multiple distortion effects showing the effectiveness of the proposed adaptive equalization techniques.

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18

Li, Yin Xue, Jun Zhang, and Yong Feng Zhi. "Study on UWB Channel Equalization with Adaptive Gain Affine Projection Algorithm." Applied Mechanics and Materials 220-223 (November 2012): 2121–28. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2121.

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A new equalization technology study with adaptive affine projection algorithm, aiming at the inter symbol interferences in the UWB channels was presented specially for time-hopping UWB (TH-UWB) systems. The computational complexity and convergence rate of the APA-AG algorithm was compared with the traditional algorithms. The simulation results show that this method improves the convergence rate and has a good stability. And the equalizer with the affine projection algorithm using adaptive gain is better than the RLS equalizer and the LMS equalizer.

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19

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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20

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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21

Kato, S., M. Hori, Y. Kawabe, and Y. Fukushima. "An adaptive equalizer for R-DAT." IEEE Transactions on Consumer Electronics 35, no. 3 (1989): 520–27. http://dx.doi.org/10.1109/30.44312.

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22

Chen, S., B. Mulgrew, and S. McLaughlin. "Adaptive Bayesian equalizer with decision feedback." IEEE Transactions on Signal Processing 41, no. 9 (1993): 2918–27. http://dx.doi.org/10.1109/78.236513.

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23

Rupp, Markus. "Convergence Properties of Adaptive Equalizer Algorithms." IEEE Transactions on Signal Processing 59, no. 6 (June 2011): 2562–74. http://dx.doi.org/10.1109/tsp.2011.2121905.

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24

Wu, Yanbo, Yan Yao, Ning Wang, and Min Zhu. "Deep Learning-Based Timing Offset Estimation for Deep-Sea Vertical Underwater Acoustic Communications." Applied Sciences 10, no. 23 (December 3, 2020): 8651. http://dx.doi.org/10.3390/app10238651.

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This study proposes a novel receiver structure for underwater vertical acoustic communication in which the bias in the correlation-based estimation for the timing offset is learned and then estimated by a deep neural network (DNN) to an accuracy that renders subsequent use of equalizers unnecessary. For a duration of 7 s, 15 timing offsets of the linear frequency modulation (LFM) signals obtained by the correlation were fed into the DNN. The model was based on the Pierson–Moskowitz (PM) random surface height model with a moderate wind speed and was further verified under various wind speeds and experimental waveforms. This receiver, embedded with the DNN model, demonstrated lower complexity and better performance than the adaptive equalizer-based receiver. The 5000 m depth deep-sea experimental data show the superiority of the proposed combination of DNN-based synchronization and the time-invariant equalizer.

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25

Kang, Heau-Jo. "Performance Analysis of Adaptive OFDM Systems using Adaptive Equalizer." Journal of Digital Contents Society 12, no. 3 (September 30, 2011): 355–60. http://dx.doi.org/10.9728/dcs.2011.12.3.355.

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26

JIANG, HONG RUI, and KYUNG SUP KWAK. "ON MODIFIED COMPLEX RECURRENT NEURAL NETWORK ADAPTIVE EQUALIZER." Journal of Circuits, Systems and Computers 11, no. 01 (February 2002): 93–101. http://dx.doi.org/10.1142/s0218126602000276.

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A new modified version called decision feedback complex recurrent neural network equalizer (DFCRNNE) is proposed with the study of complex recurrent neural network equalizer (CRNNE). Based on DFCRNNE, a modified real time recurrent learning (CRTRL) algorithm is developed. Simulation results show that DFCRNNE has better performance than CRNNE based on traditional CRTRL algorithm2 in complex nonlinear channels with severe intersymbol interference (ISI) and nonlinear distortion.

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27

Et. al., Rajender Udutha ,. "Tunable Sub Threshold Logic Design Through Adaptive Feedback Equalization." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (April 10, 2021): 1540–45. http://dx.doi.org/10.17762/turcomat.v12i2.1430.

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An Efficient tunable subthreshold logic circuit planned by utilizing adaptive feedback equalization circuit. This circuit utilized in the Ladner Fischer adder. This circuit utilized in a successive advanced logic circuit to moderate the cycle variety impacts and lessen the prevailing spillage energy part in the subthreshold area. Feedback equalizer circuit changes the switching edge of its inverter. It depends on the output of the flip-flop in the past cycle to lessen the charging and releasing season of the flip-flop's information capacitance. Besides, the more modest info capacitance of the feedback equalizer lessens the switching season of the last door in the combinational logic block. Likewise present point by point energy-performance models of the adaptive feedback equalizer circuit.

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28

Radhi Shabib Kaned. "Investigation of Phase Noise on the Performance of LMS-RLS Adaptive Equalizer." Diyala Journal of Engineering Sciences 6, no. 1 (March 1, 2013): 27–35. http://dx.doi.org/10.24237/djes.2013.06103.

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This paper investigates the effect of phase noise on equalization of communication channels using least mean square (LMS) and recursive least square (RLS) adaptive algorithms. The aim of the investigation is to mitigate inter-symbol interference (ISI) caused by the channel and to impose the bit error rate (BER) in the received signals. The equalizerusestwobasicadaptivealgorithms: LMS algorithmand RLS algorithm. Without LMS-RLS equalizer,theBER ismorethan when the system modelincludesLMS-RLS equalizer as indicated in table (1) and table (2). Equalizer algorithm is analyzed using MATLAB v.9 Communication Block Set.

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29

Krstajic, Bozo, Zdravko Uskokovic, and Ljubisa Stankovic. "Adaptive equalizer with zero-noise constrained LMS algorithm." Facta universitatis - series: Electronics and Energetics 16, no. 1 (2003): 127–35. http://dx.doi.org/10.2298/fuee0301127k.

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This paper introduces a type of zero-noise constrained LMS (ZN-CLMS) algorithm in an adaptive equalizer. It is a particular case of mismatched noise constrained LMS (NCLMS) algorithm. It is also a variant of variable step-size LMS algorithm, where the step-size rule arises naturally from the constraints. We will show here that the adaptive equalizer based on the ZN-CLMS algorithm has favorable performance. Computer simulation results are provided to support the proposed implementation of the ZNCLMS.

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ZHAO, Bin, Yu-hua ZHANG, Zhao WANG, and Feng-cheng XU. "Adaptive equalizer design based on CSPI protocol." Chinese Journal of Liquid Crystal and Displays 36, no. 2 (2021): 279–86. http://dx.doi.org/10.37188/cjlcd.2020-0147.

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31

Zhang, Sumin, Shu Li, and Donglin Su. "Adaptive support vector machine decision feedback equalizer." Journal of Systems Engineering and Electronics 22, no. 3 (June 2011): 452–61. http://dx.doi.org/10.3969/j.issn.1004-4132.2011.03.013.

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32

Itoh, N., and T. Tokumoto. "An adaptive equalizer for MUSE signal transmission." IEEE Transactions on Consumer Electronics 36, no. 3 (1990): 238–46. http://dx.doi.org/10.1109/30.103128.

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Kuo, S. M., and M. J. Ji. "Principle and application of adaptive noise equalizer." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 41, no. 7 (July 1994): 471–74. http://dx.doi.org/10.1109/82.298380.

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34

Mulgrew, B., and C. Cowan. "An adaptive Kalman equalizer: Structure and performance." IEEE Transactions on Acoustics, Speech, and Signal Processing 35, no. 12 (December 1987): 1727–35. http://dx.doi.org/10.1109/tassp.1987.1165091.

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35

Itoh, Nobuo, and Terumasa Tokumoto. "Adaptive MUSE signal equalizer for CATV reciever." Journal of the Institute of Television Engineers of Japan 44, no. 6 (1990): 791–94. http://dx.doi.org/10.3169/itej1978.44.791.

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36

EWEDA, E., and F. MEHANY. "A PROPOSED FREQUENCY DOMAIN SELF ADAPTIVE EQUALIZER." International Conference on Aerospace Sciences and Aviation Technology 1, CONFERENCE (May 1, 1985): 1–10. http://dx.doi.org/10.21608/asat.1985.26592.

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Eweda, Eweda, Safwat El-Habiby, and M. Bassiouney. "A SELF ADAPTIVE EQUALIZER WITH RAPID ACQUISITION." International Conference on Aerospace Sciences and Aviation Technology 2, CONFERENCE (April 1, 1987): 1–11. http://dx.doi.org/10.21608/asat.1987.26207.

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38

Yu Gong and C. F. N. Cowan. "A self-structured adaptive decision feedback equalizer." IEEE Signal Processing Letters 13, no. 3 (March 2006): 169–72. http://dx.doi.org/10.1109/lsp.2005.862601.

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39

Koizumi, Ryo, Teruyuki Miyajima, and Kazuo Yamanaka. "Constrained blind equalizer using adaptive nonlinear filter." Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 87, no. 3 (2003): 17–29. http://dx.doi.org/10.1002/ecjc.10145.

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40

Oh, Deock Gil, Jin Young Choi, and Choong Woong Lee. "Adaptive nonlinear equalizer with reduced computational complexity." Signal Processing 47, no. 3 (December 1995): 307–17. http://dx.doi.org/10.1016/0165-1684(95)00117-4.

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41

Oh, Kil Nam. "An Adaptive Blind Equalizer Based on Dynamic Error Signal Generation Using Equalized Output State." Journal of the Institute of Electronics and Information Engineers 50, no. 7 (July 25, 2013): 52–58. http://dx.doi.org/10.5573/ieek.2013.50.7.052.

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42

Wang, Haide, Ji Zhou, Yizhao Wang, Jinlong Wei, Weiping Liu, Changyuan Yu, and Zhaohui Li. "Optimization Algorithms of Neural Networks for Traditional Time-Domain Equalizer in Optical Communications." Applied Sciences 9, no. 18 (September 18, 2019): 3907. http://dx.doi.org/10.3390/app9183907.

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Neural networks (NNs) have been successfully applied to channel equalization for optical communications. In optical fiber communications, the linear equalizer and the nonlinear equalizer with traditional structures might be more appropriate than NNs for performing real-time digital signal processing, owing to its much lower computational complexity. However, the optimization algorithms of NNs are useful in many optimization problems. In this paper, we propose and evaluate the tap estimation schemes for the equalizer with traditional structures in optical fiber communications using the optimization algorithms commonly used in the NNs. The experimental results show that adaptive moment estimation algorithm and batch gradient descent method perform well in the tap estimation of equalizer. In conclusion, the optimization algorithms of NNs are useful in the tap estimation of equalizer with traditional structures in optical communications.

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43

Kobayashi, Masaki, Yasunori Nagasaka, Yasutomo Kinugasa, Naoto Sasaoka, and Yoshio Itoh. "A Fast SSCF Adaptive Algorithm and Its Application to Adaptive Equalizer." IEEJ Transactions on Electronics, Information and Systems 132, no. 6 (2012): 991–96. http://dx.doi.org/10.1541/ieejeiss.132.991.

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Nakayama, K., Y. Sato, and Y. Kuraishi. "Design techniques for switched-capacitor adaptive line equalizer." IEEE Transactions on Circuits and Systems 32, no. 8 (August 1985): 759–66. http://dx.doi.org/10.1109/tcs.1985.1085792.

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Sasaki, Norio, Tasuku Hanaumi, Takeshi Oda, and Fumiyuki Adachi. "Adaptive Equalizer for Digital Power Line Carrier Systems." IEEJ Transactions on Electronics, Information and Systems 134, no. 2 (2014): 258–66. http://dx.doi.org/10.1541/ieejeiss.134.258.

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Oh, Deock Gil, Jin Young Choi, and Choong Woong Lee. "Computationally Efficient Fuzzy Adaptive Equalizer for Nonlinear Channels." Journal of Intelligent and Fuzzy Systems 4, no. 1 (1996): 65–73. http://dx.doi.org/10.3233/ifs-1996-4105.

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Kim, D. W., S. H. Han, M. S. Eun, J. S. Choi, and Y. S. Cho. "An adaptive decision feedback equalizer using error feedback." IEEE Transactions on Consumer Electronics 42, no. 3 (1996): 468–77. http://dx.doi.org/10.1109/30.536144.

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Guangyu Evelina Zhang and M. M. Green. "A 10 Gb/s BiCMOS adaptive cable equalizer." IEEE Journal of Solid-State Circuits 40, no. 11 (November 2005): 2132–40. http://dx.doi.org/10.1109/jssc.2005.857354.

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Le, M. Q., P. J. Hurst, and J. P. Keane. "An adaptive analog noise-predictive decision-feedback equalizer." IEEE Journal of Solid-State Circuits 37, no. 2 (2002): 105–13. http://dx.doi.org/10.1109/4.982416.

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Song, Seongwook, and Kyungho Kim. "Signal Regeneration Adaptive Equalizer for Fast Fading Environment." IEEE Transactions on Communications 59, no. 8 (August 2011): 2162–71. http://dx.doi.org/10.1109/tcomm.2011.060911.090106.

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