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A Fast Algorithm for Matrix-Variable Triconvex Optimization With Application to Blind Image Deblurring 认领 引用
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作者 Songchuan Zhang Liqing Huang +1 位作者 Youshen Xia Jun Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第5期1184-1206,共23页
Matrix-variable triconvex optimization is a significant generalization of vector-variable triconvex or biconvex optimization and has been found to have popular applications.To reduce computation time and storage requi... Matrix-variable triconvex optimization is a significant generalization of vector-variable triconvex or biconvex optimization and has been found to have popular applications.To reduce computation time and storage requirements,this paper presents a matrix-form iterative method for quickly solving matrix-variable constrained triconvex optimization problems.The proposed method is based on a matrix-form alternating projection iteration scheme in the form of matrix state spaces,where an efficient line search strategy is adopted by exploiting the optimality conditions of the problem for a larger step length.Compared with the existing vector-form alternating projection gradient method,the proposed method reduces storage requirements and computational cost,and thus is more computationally efficient.Each sequence generated by the proposed method is guaranteed to be globally convergent to a partial optimum under mild conditions.Finally,the proposed method is effectively applied to blind image deblurring problems.Computed results show that the proposed algorithm is superior to related iterative algorithms in terms of computation time and solution quality. 展开更多
关键词 Blind image deblurring global convergence matrixform iterative method matrix variable multiconvex optimization
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TLS Blind Recognition Algorithm of LDPC Codes 认领 引用
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作者 Ning Xiaoyan Sun Jingjing +1 位作者 Wang Zhenduo Sun Zhiguo 《China Communications》 SCIE EI CSCD 2026年第2期112-121,共10页
Blind recognition of low-density paritycheck(LDPC)codes has gradually attracted more attention with the development of military and civil communications.However,in the case of the paritycheck matrices with relatively ... Blind recognition of low-density paritycheck(LDPC)codes has gradually attracted more attention with the development of military and civil communications.However,in the case of the paritycheck matrices with relatively high row weights,the existing blind recognition algorithms based on a candidate set generally perform worse.In this paper,we propose a blind recognition method for LDPC codes,called as tangent function assisted least square(TLS)method,which improves recognition performances by constructing a new cost function.To characterize the constraint degree among received vectors and paritycheck vectors,a feature function based on tangent function is constructed in the proposed algorithm.A cost function based on least square method is also established according to the feature function values satisfying the parity-check relationship.Moreover,the minimum average value in TLS is obtained on the candidate set.Numerical analysis and simulation results show that recognition performances of TLS algorithm are consistent with theoretical results.Compared with existing algorithms,the proposed method possesses better recognition performances. 展开更多
关键词 blind recognition cost function least square low-density parity-check(LDPC)codes
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Blind radar signal separation algorithm based on third-order degree of cyclostationarity criteria 认领 引用
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作者 FAN Xiangyu LIU Bin +2 位作者 DONG Danna CHEN You WANG Yuancheng 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第6期1441-1453,共13页
Separation and recognition of radar signals is the key function of modern radar reconnaissance,which is of great sig-nificance for electronic countermeasures and anti-countermea-sures.In order to improve the ability o... Separation and recognition of radar signals is the key function of modern radar reconnaissance,which is of great sig-nificance for electronic countermeasures and anti-countermea-sures.In order to improve the ability of separating mixed signals in complex electromagnetic environment,a blind source separa-tion algorithm based on degree of cyclostationarity(DCS)crite-rion is constructed in this paper.Firstly,the DCS criterion is con-structed by using the cyclic spectrum theory.Then the algo-rithm flow of blind source separation is designed based on DCS criterion.At the same time,Givens matrix is constructed to make the blind source separation algorithm suitable for multiple sig-nals with different cyclostationary frequencies.The feasibility of this method is further proved.The theoretical and simulation results show that the algorithm can effectively separate and re-cognize common multi-radar signals. 展开更多
关键词 blind signal separation cyclostationary frequency Givens matrix degree of cyclostationarity(DCS)blind source separation algorithm
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Algorithm for source recovery in underdetermined blind source separation based on plane pursuit 认领 引用 被引量：2
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作者 FU Weihong WEI Juan +1 位作者 LIU Naian CHEN Jiehu 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2018年第2期223-228,共6页
In order to achieve accurate recovery signals under the underdetermined circumstance in a comparatively short time,an algorithm based on plane pursuit(PP) is proposed. The proposed algorithm selects the atoms accordin... In order to achieve accurate recovery signals under the underdetermined circumstance in a comparatively short time,an algorithm based on plane pursuit(PP) is proposed. The proposed algorithm selects the atoms according to the correlation between received signals and hyper planes, which are composed by column vectors of the mixing matrix, and uses these atoms to recover source signals. Simulation results demonstrate that the PP algorithm has low complexity and higher accuracy as compared with basic pursuit(BP), orthogonal matching pursuit(OMP), and adaptive sparsity matching pursuit(ASMP) algorithms. 展开更多
关键词 underdetermined blind source separation(UBSS) source recovery greedy algorithm plane pursuit
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Widely linear UKF constant modulus algorithm for blind adaptive beamforming 认领 引用 被引量：1
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作者 Huaming Qian Ke Liu +2 位作者 Long Li Linchen Qian Junda Ma 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2017年第3期413-423,共11页
Based on a uniform linear array, a new widely linear unscented Kalman filter-based constant modulus algorithm (WL-UKF-CMA) for blind adaptive beamforming is proposed. The new algorithm is designed according to the con... Based on a uniform linear array, a new widely linear unscented Kalman filter-based constant modulus algorithm (WL-UKF-CMA) for blind adaptive beamforming is proposed. The new algorithm is designed according to the constant modulus criterion and takes full advantage of the noncircular property of the signal of interest (SOI), significantly increasing the output signal-to interference-plus-noise ratio (SINR), enhancing the convergence speed and decreasing the steady-state misadjustment. Since it requires no known training data, the proposed algorithm saves a large amount of the available spectrum. Theoretical analysis and simulation results are presented to demonstrate its superiority over the conventional linear least mean square-based CMA (L-LMS-CMA), the conventional linear recursive least square-based CMA (L-RLS-CMA), WL-LMS-CMA, WL-RLS-CMA and L-UKF-CMA. 展开更多
关键词 widely linear filtering blind beamforming noncircular signals constant modulus algorithm unscented Kalman filtering
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Blind Equalization Algorithm Based on MCMA and DSE-CMA 认领 引用 被引量：2
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作者 GENG Nian XUE Ni RU Guobao 《Wuhan University Journal of Natural Sciences》 CAS 2008年第1期67-70,共4页
A new blind equalization algorithm based on the modified constant modulus algorithm （MCMA） and dithered signederror constant modulus algorithm （DSE-CMA） is proposed. This dithered signed-error MCMA （DSE-MCMA） ca... A new blind equalization algorithm based on the modified constant modulus algorithm （MCMA） and dithered signederror constant modulus algorithm （DSE-CMA） is proposed. This dithered signed-error MCMA （DSE-MCMA） can not only reduce the computational complexity, but also recover the phase rotation in the complex channel. Simulation results have verified the analysis and indicated the good property of DSE-MCMA. 展开更多
关键词 blind equalization modified constant modulus algorithm （MCMA）, intersymbol interference
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An Orthogonal Wavelet Transform Fractionally Spaced Blind Equalization Algorithm Based on the Optimization of Genetic Algorithm 认领 引用
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作者 廖娟 郭业才 季童莹 《Defence Technology（防务技术）》 CAS 2011年第2期65-71,共7页
An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square er... An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square error and local convergence of traditional constant modulus blind equalization algorithm(CMA).The proposed algorithm can reduce the signal autocorrelation through the orthogonal wavelet transform of input signal of fractionally spaced blind equalizer,and decrease the possibility of CMA local convergence by using the global random search characteristics of genetic algorithm to optimize the equalizer weight vector.The proposed algorithm has the faster convergence rate and smaller mean square error compared with FSE and WT-FSE.The efficiency of the proposed algorithm is proved by computer simulation of underwater acoustic channels. 展开更多
关键词 information processing technique genetic algorithm orthogonal wavelet transform fractionally spaced equalizer blind equalization underwater acoustic channel
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New subspace algorithm for blind channel estimation in OFDM systems 认领 引用
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作者 黄学军 余松煜 毕厚杰 《Journal of Southeast University(English Edition)》 EI CAS 2005年第2期132-135,共4页
In order to increase the transmission efficiency,a subspace-based algorithm for blind channel estimation using second-order statistics is proposed in orthogonal frequency division multiplexing (OFDM) systems.Because t... In order to increase the transmission efficiency,a subspace-based algorithm for blind channel estimation using second-order statistics is proposed in orthogonal frequency division multiplexing (OFDM) systems.Because the transmission equation of OFDM systems does not exactly have the desired structure to directly derive a subspace algorithm,the algorithm first divides the OFDM signals into three parts,then,by exploiting the redundancy introduced by the cyclic prefix (CP) in OFDM signals,a new equation with Toeplitz channel matrix is derived.Based on the equation,a new blind subspace algorithm is developed.Toeplitz structure eases the derivation of the subspace algorithm and practical computation.Moreover the algorithm does not change the existing OFDM system,is robust to channel order overdetermination,and the channel zero locations.The performances are demonstrated by simulation results. 展开更多
关键词 orthogonal frequency division multiplexing (OFDM) blind channel estimation subspace algorithm
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ADAPTIVE BLIND ESTIMATION ALGORITHM FOR OFDM-MIMO RADIO SYSTEMS OVER MULTIPATH CHANNELS 认领 引用
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作者 DuJiang PengQicong 《Journal of Electronics(China)》 2004年第6期441-448,共8页
This paper investigates the blind algorithm for channel estimation of Orthogonal Frequency Division Multiplexing-Multiple Input Multiple Output (OFDM-MIMO) wireless communication system using the subspace decompositio... This paper investigates the blind algorithm for channel estimation of Orthogonal Frequency Division Multiplexing-Multiple Input Multiple Output (OFDM-MIMO) wireless communication system using the subspace decomposition of the channel received complex baseband signals and proposes a new two-stage blind algorithm. Exploited the second-order cyclostationarity inherent in OFDM with cyclic prefix and the characteristics of the phased antenna, the practical HIPERLAN/2 standard based OFDM-MIMO simulator is established with the sufficient consideration of statistical correlations between the multiple antenna channels under wireless wideband multipath fading environment, and a new two-stage blind algorithm is formulated using rank reduced subspace channel matrix approximation and adaptive Constant Modulus (CM)criterion. Simulation results confirm the theoretical analysis and illustrate that the proposed algorithm is capable of tracking matrix channel variations with fast convergence rate and improving acceptable overall system performance over various common wireless and mobile communication links. 展开更多
关键词 Orthogonal Frequency Division Multiplexing-Multiple Input Multiple Output(OFDM-MIMO) system HIPERLAN/2 Two-stage blind algorithm Constant Modulus Algorithm (CMA) Matrix channel estimation Convergence
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Blind Equalization Based on RLS Algorithm Using Adaptive Forgetting Factor for Underwater Acoustic Channel 认领 引用 被引量：8
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作者 肖瑛 殷福亮 《China Ocean Engineering》 SCIE EI CSCD 2014年第3期401-408,共8页
Blind equalization based on adaptive forgetting factor, recursive least squares （RLS） with constant modulus algorithm （CMA）, is investigated. The cost function of CMA is simplified to meet the second norm form to ... Blind equalization based on adaptive forgetting factor, recursive least squares （RLS） with constant modulus algorithm （CMA）, is investigated. The cost function of CMA is simplified to meet the second norm form to ensure the stability of RLS-CMA, and thus an improved RLS-CMA （RLS-SCMA） is established. To further improve its performance, a new adaptive forgetting factor RLS-SCMA （ARLS-SCMA） is proposed. In ARLS-SCMA, the forgetting factor varies with the output error of the blind equalizer during the iterative process, which leads to a faster convergence rate and a smaller steady-state error. The simulation results prove the effectiveness under the condition of the underwater acoustic channel. 展开更多
关键词 blind equalization RLS CMA underwater acoustic channel second norm form
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The Velocity Measurement of Two-phase Flow Based on Particle Swarm Optimization Algorithm and Nonlinear Blind Source Separation 认领 引用 被引量：5
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作者 吴新杰 崔春阳 +2 位作者 胡晟 李志宏 吴成东 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2012年第2期346-351,共6页
In order to overcome the disturbance of noise,this paper presented a method to measure two-phase flow velocity using particle swarm optimization algorithm,nonlinear blind source separation and cross correlation method... In order to overcome the disturbance of noise,this paper presented a method to measure two-phase flow velocity using particle swarm optimization algorithm,nonlinear blind source separation and cross correlation method.Because of the nonlinear relationship between the output signals of capacitance sensors and fluid in pipeline,nonlinear blind source separation is applied.In nonlinear blind source separation,the odd polynomials of higher order are used to fit the nonlinear transformation function,and the mutual information of separation signals is used as the evaluation function.Then the parameters of polynomial and linear separation matrix can be estimated by mutual information of separation signals and particle swarm optimization algorithm,thus the source signals can be separated from the mixed signals.The two-phase flow signals with noise which are obtained from upstream and downstream sensors are respectively processed by nonlinear blind source separation method so that the noise can be effectively removed.Therefore,based on these noise-suppressed signals,the distinct curves of cross correlation function and the transit times are obtained,and then the velocities of two-phase flow can be accurately calculated.Finally,the simulation experimental results are given.The results have proved that this method can meet the measurement requirements of two-phase flow velocity. 展开更多
关键词 particle swarm optimization nonlinear blind source separation velocity cross correlation method
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UBSS and blind parameters estimation algorithms for synchronous orthogonal FH signals 认领 引用 被引量：13
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作者 Weihong Fu Yongqiang Hei Xiaohui Li 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2014年第6期911-920,共10页
By using the sparsity of frequency hopping（FH） signals,an underdetermined blind source separation（UBSS） algorithm is presented. Firstly, the short time Fourier transform（STFT） is performed on the mixed signals. ... By using the sparsity of frequency hopping（FH） signals,an underdetermined blind source separation（UBSS） algorithm is presented. Firstly, the short time Fourier transform（STFT） is performed on the mixed signals. Then, the mixing matrix, hopping frequencies, hopping instants and the hooping rate can be estimated by the K-means clustering algorithm. With the estimated mixing matrix, the directions of arrival（DOA） of source signals can be obtained. Then, the FH signals are sorted and the FH pattern is obtained. Finally, the shortest path algorithm is adopted to recover the time domain signals. Simulation results show that the correlation coefficient between the estimated FH signal and the source signal is above 0.9 when the signal-to-noise ratio（SNR） is higher than 0 d B and hopping parameters of multiple FH signals in the synchronous orthogonal FH network can be accurately estimated and sorted under the underdetermined conditions. 展开更多
关键词 frequency hopping（FH） underdetermined blind source separation（UBSS） parameters estimation clustering
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Optimization of Truss Structures Using Nature-Inspired Algorithms with Frequency and Stress Constraints 认领 引用 被引量：1
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作者 Sanjog Chhetri Sapkota Liborio Cavaleri +3 位作者 Ajaya Khatri Siddhi Pandey Satish Paudel Panagiotis G.Asteris 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第1期436-464,共29页
Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises stru... Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises structural weight under stress and frequency constraints.Two new algorithms,the Red Kite Optimization Algorithm(ROA)and Secretary Bird Optimization Algorithm(SBOA),are utilized on five benchmark trusses with 10,18,37,72,and 200-bar trusses.Both algorithms are evaluated against benchmarks in the literature.The results indicate that SBOA always reaches a lighter optimal.Designs with reducing structural weight ranging from 0.02%to 0.15%compared to ROA,and up to 6%–8%as compared to conventional algorithms.In addition,SBOA can achieve 15%–20%faster convergence speed and 10%–18%reduction in computational time with a smaller standard deviation over independent runs,which demonstrates its robustness and reliability.It is indicated that the adaptive exploration mechanism of SBOA,especially its Levy flight–based search strategy,can obviously improve optimization performance for low-and high-dimensional trusses.The research has implications in the context of promoting bio-inspired optimization techniques by demonstrating the viability of SBOA,a reliable model for large-scale structural design that provides significant enhancements in performance and convergence behavior. 展开更多
关键词 Optimization truss structures nature-inspired algorithms meta-heuristic algorithms red kite opti-mization algorithm secretary bird optimization algorithm
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Blind Signal Separation Based on Quantum Genetic Algorithm 认领 引用
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作者 Jingjing Xu Houjin Chen +1 位作者 Ytnhang Cheng Rui Luo 《通讯和计算机（中英文版）》 2005年第9期62-66,共5页
Blind Signal Separation （BSS） is one of the typical problems in array processing and data analysis. In this paper, a novel method of blind signal separation based on Quantum Genetic Algorithm （QGA） is proposed. QG... Blind Signal Separation （BSS） is one of the typical problems in array processing and data analysis. In this paper, a novel method of blind signal separation based on Quantum Genetic Algorithm （QGA） is proposed. QGA is a more effective way in comparison with Conventional Genetic Algorithm （CGA）. 展开更多
关键词 Blind Signal Separation （BSS） Quantum Genetic Algorithm （QGA） Conventional Genetic Algorithm （CGA） Independent Component Analysis （ICA）
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Blind Channel Equalization Algorithm Based on Dual Unscented Kalman Filter for Chaotic Multi-Input Multi-Output Communication Systems 认领 引用 被引量：3
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作者 Hu Zhihui FENG Jiuchao 《Transactions of Tianjin University》 EI CAS 2012年第1期33-37,共5页
To reduce channel noise,fading,and inter-user interference effectively in the chaotic communication systems with multi-user,a blind channel equalization algorithm based on dual unscented Kalman filter algorithm is pro... To reduce channel noise,fading,and inter-user interference effectively in the chaotic communication systems with multi-user,a blind channel equalization algorithm based on dual unscented Kalman filter algorithm is proposed.Assuming that the coefficients of a multi-input multi-output (MIMO) channel can be described by an autoregressive model,two separate state-space representations are used for the signals and coefficients.Then two unscented Kalman filters are used to estimate chaotic signals and channel coefficients simultaneously.The simulation results indicate that the algorithm can effectively track the coefficients of the multi-path fading channel in chaotic MIMO communication systems at a fast convergence speed. 展开更多
关键词 chaotic MIMO system blind channel equalization unscented Kalman filter
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A novel blind deconvolution algorithm using single frequency bin 认领 引用 被引量：1
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作者 ZHANG Gui-bao LI Jia-wen LI Cong-xin 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS 2007年第8期1271-1276,共6页
Former frequency-domain blind devolution algorithms need to consider a large number of frequency bins and recover the sources in different orders and with different amplitudes in each frequency bin,so they suffer from... Former frequency-domain blind devolution algorithms need to consider a large number of frequency bins and recover the sources in different orders and with different amplitudes in each frequency bin,so they suffer from permutation and amplitude indeterminacy troubles.Based on sliding discrete Fourier transform,the presented deconvolution algorithm can directly recover time-domain sources from frequency-domain convolutive model using single frequency bin.It only needs to execute blind sepa-ration of instantaneous mixture once there are no permutation and amplitude indeterminacy troubles.Compared with former algorithms,the algorithm greatly reduces the computation cost as only one frequency bin is considered.Its good and robust per-formance is demonstrated by simulations when the signal-to-noise-ratio is high. 展开更多
关键词 Blind deconvolution Single frequency bin Convolutive mixture
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Audio-Visual Underdetermined Blind Source Separation Algorithm Based on Gaussian Potential Function 认领 引用 被引量：1
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作者 ZHANG Ye CAO Kang +2 位作者 WU Kangrui YU Tenglong ZHOU Nanrun 《China Communications》 SCIE CSCD 2014年第6期71-80,共10页
Most existing algorithms for the underdetermined blind source separation(UBSS) problem are two-stage algorithm, i.e., mixing parameters estimation and sources estimation. In the mixing parameters estimation, the previ... Most existing algorithms for the underdetermined blind source separation(UBSS) problem are two-stage algorithm, i.e., mixing parameters estimation and sources estimation. In the mixing parameters estimation, the previously proposed traditional clustering algorithms are sensitive to the initializations of the mixing parameters. To reduce the sensitiveness to the initialization, we propose a new algorithm for the UBSS problem based on anechoic speech mixtures by employing the visual information, i.e., the interaural time difference(ITD) and the interaural level difference(ILD), as the initializations of the mixing parameters. In our algorithm, the video signals are utilized to estimate the distances between microphones and sources, and then the estimations of the ITD and ILD can be obtained. With the sparsity assumption in the time-frequency domain, the Gaussian potential function algorithm is utilized to estimate the mixing parameters by using the ITDs and ILDs as the initializations of the mixing parameters. And the time-frequency masking is used to recover the sources by evaluating the various ITDs and ILDs. Experimental results demonstrate the competitive performance of the proposed algorithm compared with the baseline algorithms. 展开更多
关键词 underdetermined blind sourceseparation interaural time difference interaural level difference visual information Gaussian potential function
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A Blind Watermarking Algorithm Resisting to Geometric Transforms Based on SVD 认领 引用 被引量：2
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作者 LI Xiuguang YANG Xiaoyuan 《Wuhan University Journal of Natural Sciences》 CAS 2011年第6期487-492,共6页
A new watermarking algorithm resisting to geometric transformation based on singular value decomposition （SVD） in logarithm polar coordinate is proposed. The log-polar mapping （LPM） is used to resist rotation and ... A new watermarking algorithm resisting to geometric transformation based on singular value decomposition （SVD） in logarithm polar coordinate is proposed. The log-polar mapping （LPM） is used to resist rotation and scaling attacks, and the odd-even quantization algorithm is used to embed watermark so it can be extracted without the original host image. The experiments show that the proposed algorithm not only resists various geomet- ric attacks but also is robust enough to the common signal processing. 展开更多
关键词 blind watermarking singular value decomposition（SVD） logarithm polar coordinate resist to geometric transform
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A K-means clustering based blind multiband spectrum sensing algorithm for cognitive radio 认领 引用 被引量：5
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作者 LEI Ke-jun TAN Yang-hong +1 位作者 YANG Xi WANG Han-rui 《Journal of Central South University》 SCIE EI CAS CSCD 2018年第10期2451-2461,共11页
In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorith... In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorithm is used to identify the occupied subband set(OSS)and the idle subband set(ISS),and then the location and number information of the occupied channels are obtained according to the elements in the OSS.Compared with the classical BMSS methods based on the information theoretic criteria(ITC),the new method shows more excellent performance especially in the low signal-to-noise ratio(SNR)and the small sampling number scenarios,and more robust detection performance in noise uncertainty or unequal noise variance applications.Meanwhile,the new method performs more stablely than the ITC-based methods when the occupied subband number increases or the primary signals suffer multi-path fading.Simulation result verifies the effectiveness of the proposed method. 展开更多
关键词 cognitive radio(CR) blind multiband spectrum sensing(BMSS) K-means clustering(KMC) occupied subband set(OSS) idle subband set(ISS) information theoretic criteria(ITC) noise uncertainty
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A Block-Adaptive Blind Separation Algorithm for Post-Nonlinear Mixture of Sub- and Super-Gaussian Signals 认领 引用 被引量：1
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作者 陈阳 杨绿溪 何振亚 《Journal of Southeast University(English Edition)》 CAS 2000年第2期1-9,共9页
The problem of blind separation of signals in post nonlinear mixture is addressed in this paper. The post nonlinear mixture is formed by a component wise nonlinear distortion after the linear mixture. Hence a nonlinea... The problem of blind separation of signals in post nonlinear mixture is addressed in this paper. The post nonlinear mixture is formed by a component wise nonlinear distortion after the linear mixture. Hence a nonlinear adjusting part placed in front of the linear separation structure is needed to compensate for the distortion in separating such signals. The learning rules for the post nonlinear separation structure are derived by a maximum likelihood approach. An algorithm for blind separation of post nonlinearly mixed sub and super Gaussian signals is proposed based on some previous work. Multilayer perceptrons are used in this algorithm to model the nonlinear part of the separation structure. The algorithm switches between sub and super Gaussian probability models during learning according to a stability condition and operates in a block adaptive manner. The effectiveness of the algorithm is verified by experiments on simulated and real world signals. 展开更多
关键词 blind separation neural networks nonlinear mixture sub and super Gaussian
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