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Volume 31 Issue 7
Dec.  2010
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Tan Bei-hai, Zhao Min, Xie Sheng-li. Blind Separation Algorithms of BPSK Signals by Estimating Source Number[J]. Journal of Electronics & Information Technology, 2009, 31(7): 1624-1629. doi: 10.3724/SP.J.1146.2008.00992
Citation: Tan Bei-hai, Zhao Min, Xie Sheng-li. Blind Separation Algorithms of BPSK Signals by Estimating Source Number[J]. Journal of Electronics & Information Technology, 2009, 31(7): 1624-1629. doi: 10.3724/SP.J.1146.2008.00992

Blind Separation Algorithms of BPSK Signals by Estimating Source Number

doi: 10.3724/SP.J.1146.2008.00992
  • Received Date: 2008-08-09
  • Rev Recd Date: 2009-03-17
  • Publish Date: 2009-07-19
  • At present, there exist a lot of algorithms of blind separation, among which there are few algorithms focusing on blind separation of digital signals and estimating source number. To solve the problem, this paper proposes a novel algorithm to solve the blind separation problem of BPSK signals. First, according to characteristics of observations, the algorithm to estimate the source number is given in noise circumstance and no noise circumstance. Second, mixing matrix is gotten by using the relation of observations, which is also proved feasible. Finally, the source signals are recovered by permutations and sign changes of their rows, which are allowed in blind separation. It is well shown that the algorithms are excellent and feasible to estimate the mixed matrix and recover source in the last simulation.
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  • Naini F M, Mohimani G H, Zadeh M B, and Jutten C.Estimating the mixing matrix in sparse componentanalysis(SCA) based on partial k-dimensional subspaceclustering[J].Neurocomputing.2008, 71(10):2330-2343[2]Tichavsky P, Koldovsky Z, Yeredor A, Gomez-herrero G,and Doron E. A hybrid technique for blind separation ofnon-gaussian and time-correlated sources using amulticomponent approach[J].IEEE Transactions onNeural Networks.2008, 19(3):421-430[3]Sun T Y, Liu C C, Hsieh S T, and Tsai S J. Blindseparation with unknown number of sources based onauto-trimmed neural network[J].Neurocomputing.2008,71(10):2271-2280[4]He Z S, Xie S L, Ding S X, and Cichocki A. Convolutiveblind source separation in the frequency domain based onsparse representation[J].IEEE Transactions on Audio,Speech, and Language Processing.2007, 15(5):1551-1563[5]Lin Q H, Yin F L, Mei T M, and Liang H. A blind sourceseparation-based method for multiple imagesencryption[J].Image and Vision Computing.2008, 26(6):788-798[6]He Z S, Xie S L, Zhang L Q, and Cichocki A. A note onLewicki-Sejnowski gradient for learning overcompleterepresentations[J].Neural Computation.2008, 20(3):636-643[7]Hyvarinen A and Oja E. Independent component analysis:algorithms and applications[J].Neural Networks.2000,13(5):411-430[8]Anand K, Mathew G, and Reddy V U. Blind separation ofmultiple co-channel BPSK signals arriving at an antennaarray[J].IEEE Signal Processing Letters.1995, 2(9):176-178[9]Lee C C and Lee J H. An effient method for blind digitalsignal separation of array data[J].Signal Processing.1999,77(2):229-234[10]Li Y Q, Cichocki A, and Zhang L Q. Blind separation andextraction of binary sources[J]. Communication andComputer Sciences, 2003, 86(3): 580-590.[11]Alle J and Veen V D. Analytical method for blind binarysignal separation[J].IEEE Transactions on Signal Processing.1997, 45(4):1078-1082[12]Talwar S, Viberg M, and Paulraj A. Blind estimation ofsynchronous co-channel digital signals using an antennaarray. Part I: algorithms[J]. IEEE Transactions on SignalProcessing. 1996, 44(5): 1184-1197.[13]Swindlehurst A and Yang J. Using least squares to improveblind signal copy performance[J].IEEE Signal ProcessingLetters.1994, 1(5):80-82[14]Hansen L K and Xu G. A hyperplane-based algorithm for thedigital co-channel communications problem[J].IEEETransactions on. Information Theory.1997, 43(5):1536-1548[15]Li Q Y, Bai E W W, and Ding Z. Blind source separation ofsignals with known alphabets using -approximationalgorithms[J].IEEE Transactions on Signal Processing.2003,51(1):1-10[16]Wong C C and Chen C C. A hybrid clustering and gradientdescent approach fuzzy modeling[J]. IEEE Transactions onSystem, Man, and Cybernetics-Part B, 1999, 29(6): 686-693.
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