Multistage decomposition algorithm for blind source separation

A new algorithm for blind source separation is proposed, which only extracts the single independent component at each stage. The single independent component is acquired by an iterative algorithm for searching for the optimal solution of the defined cost function. Moreover, all the independent components are obtained by systematic multistage decomposition and multistage reconstruction. When there is spatially colored noise, the performance of this algorithm is advantageous over jointly approximated diagonalization of eigen-matrices (JADE). Simulated results show that if the number of source signals is more than 25, its computational complexity is lower than that of JADE.     

Feature Extraction of Localized Scattering Centers Using the Modified TLS-Prony Algorithm and Its Applications

Feature Extraction of Localized Scattering Centers Using the Modified TLS-Prony Algorithm and Its Applications~~~~     

Using evolutionary computation to solve problems in nonparametric regression

This paper studies evolutionary mechanism of parameter selection in the construction of weight function for Nearest Neighbour Estimate in nonparametric regression. Construct an algorithm which adaptively evolves fine weight and makes good prediction about unknown points. The numerical experiments indicate that this method is effective. It is a meaningful discussion about practicability of nonparametric regression and methodology of adaptive model-building. Supported by the National Natural Science Foundation and 863 High Technology Project of China Ding Lixin: born in 1967, Ph.D. graduate student     

Fast synchronization scheme for SMCC+system with lower SNR

1.INTRODUCTION IntheexistingdigitalTVterrestrialbroadcasting standards,therearethetrellis coded8 levelvestigial side band(8 VSB)modulationsystemdevelopedby advancedtelevisionsystemscommittee(ATSC)[1], thecodedorthogonalfrequencydivisionmultiplexing (COFDM)modulationwasdoptedinthedigitalvideo terrestrialbroadcasting(DVB T)[2]standardandthe bandwidthsegmentedtransmission(BST) OFDM systemforterrestrialintegratedservicedigitalbroad casting(ISDB T)[3].Inaword,eachsystemhasits advan…     

略论20世纪七八十年代之交乡村小说创作的文化盲点

20世纪七八十年代之交乡村小说的文化盲点主要存在于对极左专制路线的批判和对延续一个时代的激进政治思潮的反思方面。首先，这一阶段内的许多作品都将一个时代的偏颇与失误归咎于少数人的所作所为，而忽略了时代的偏颇与失误出现的历史必然性。其次，这一阶段内的许多作品在描写一个时代的狂热与荒谬时存在着概念化的倾向，作品没有完全揭示狂热与荒谬所包含的历史文化内涵及狂热与荒谬得以存在的女化依托。     

Neural Blind Beamformer for Cyclostationary Signals

1 .INTRODUCTIONBeamforming[1]is another name for spatial filteringwhere an array of sensors together with appropriatesignal processing can either direct or block the radia-tion or the reception of signalsin specified directions .Conventional beamforming approaches require a refer-ence signal or accurate knowledge of the array re-sponse vector corresponding to the desired signal .Ifthe array response vector is not known precisely,theperformance of conventional beamforming techniquescan be s…     

新疆大红柳滩地区俘虏沟花岗伟晶岩成矿特征

西昆仑?喀喇昆仑位于特提斯构造域北缘,该地区通过多年的基础地质调查和找矿勘查,已发现多处铁矿、铅锌矿、锰矿矿床。通过详细野外地质调查在新疆喀刺昆仑和田县俘虏沟地区发现一处中型锂铷稀有金属矿床。该矿床属于花岗伟晶岩型,脉体倾向北东30°-50°或西南204°-240°,倾角39°-78°,矿体规模最大者宽约7-8m,北西-南东向延伸1.2Km。Li2O平均品位1.1%~3.3%,Rb2O平均伴生品位为0.04%~0.12%,估算资源量(334)Li2O为8.68万吨,Rb2O为1698.58吨,达到中型锂铷多金属矿床规模。俘虏沟地区中型锂铷多金属矿床的发现,表明在该区域具有形成稀有金属矿产的潜力。     

单用户无线信道盲均衡算法综述

无线信道盲均衡是近年来通信信号处理领域的研究热点。简要介绍了单用户无线信道盲均衡的数学描述,综述了基于Bussgang技术、高阶统计量、二阶矩、神经网络理论、信息理论盲源分离等几种典型算法,介绍了盲均衡的发展历程、研究现状,最后提出了发展半盲均衡算法及将信息熵理应用于盲均衡算法等有价值的研究方向。     

New blind adaptive approach to multiuser detection in CDMA systems

Due to a number of advantages, blind adaptive multiuser detector has become a research hotspot in recent years. But low convergence rate problem occurs to many blind adaptive algorithms. A new blind adaptive approach to multiuser detection is presented. The simulation results show that by reasonably choosing time varying step size, the proposed detector can not only improve the convergence rate, but also reduce the bit error rate (BER) of the system, and so it can effectively improve the system performance with less computational cost.     

Blind separation of sources in nonlinear convolved mixture based on a novel network

Blind separation of independent sources from their nonlinear convoluted mixtures is a more realistic problem than from linear ones. A solution to this problem based on the Entropy Maximization principle is presented. First we propose a novel two-layer network as the de-mixing system to separate sources in nonlinear convolved mixture. In output layer of our network we use feedback network architecture to cope with convoluted mixtures. Then we derive learning algorithms for the two-layer network by maximizing the information entropy. Based on the comparison of the computer simulation results, it can be concluded that the proposed algorithm has a better nonlinear convolved blind signal separation effect than the H.H. Y' s algorithm.