{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:01:38Z","timestamp":1760234498092,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2021,5,26]],"date-time":"2021-05-26T00:00:00Z","timestamp":1621987200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>As the main method of information transmission, it is particularly important to ensure the security of speech communication. Considering the more complex multipath channel transmission situation in the wireless communication of speech signals and separating or extracting the source signal from the convolutional signal are crucial steps in obtaining source information. In this paper, chaotic masking technology is used to guarantee the transmission safety of speech signals, and a fast fixed-point independent vector analysis algorithm is used to solve the problem of convolutional blind source separation. First, the chaotic masking is performed before the speech signal is sent, and the convolutional mixing process of multiple signals is simulated by impulse response filter. Then, the observed signal is transformed to the frequency domain by short-time Fourier transform, and instantaneous blind source separation is performed using a fast fixed-point independent vector analysis algorithm. The algorithm can preserve the high-order statistical correlation between frequencies to solve the permutation ambiguity problem in independent component analysis. Simulation experiments show that this algorithm can efficiently complete the blind extraction of convolutional signals, and the quality of recovered speech signals is better. It provides a solution for the secure transmission and effective separation of speech signals in multipath transmission channels.<\/jats:p>","DOI":"10.3390\/a14060165","type":"journal-article","created":{"date-parts":[[2021,5,26]],"date-time":"2021-05-26T10:30:32Z","timestamp":1622025032000},"page":"165","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["An Efficient Convolutional Blind Source Separation Algorithm for Speech Signals under Chaotic Masking"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1933-3003","authenticated-orcid":false,"given":"Shiyu","family":"Guo","sequence":"first","affiliation":[{"name":"Electrical Engineering College, Heilongjiang University, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengna","family":"Shi","sequence":"additional","affiliation":[{"name":"Electrical Engineering College, Heilongjiang University, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanqi","family":"Zhou","sequence":"additional","affiliation":[{"name":"Electrical Engineering College, Heilongjiang University, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiayin","family":"Yu","sequence":"additional","affiliation":[{"name":"Electrical Engineering College, Heilongjiang University, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3161-7225","authenticated-orcid":false,"given":"Erfu","family":"Wang","sequence":"additional","affiliation":[{"name":"Electrical Engineering College, Heilongjiang University, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1016\/j.compeleceng.2018.04.018","article-title":"Covert communication model for speech signals based on an indirect and adaptive encryption technique","volume":"68","author":"Shahadi","year":"2018","journal-title":"Comput. Electr. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1269","DOI":"10.1016\/j.procs.2018.04.342","article-title":"A Speech Privacy Protection Method Based on Sound Masking and Speech Corpus","volume":"131","author":"Qi","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.compeleceng.2019.05.008","article-title":"A survey of voice and communication protection solutions against wiretapping","volume":"77","author":"Ntantogian","year":"2019","journal-title":"Comput. Electr. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.oceaneng.2018.01.035","article-title":"Time reversal MFSK acoustic communication in underwater channel with large multipath spread","volume":"152","author":"Cao","year":"2018","journal-title":"Ocean Eng."},{"key":"ref_5","first-page":"1150","article-title":"Student\u2019s t Source and Mixing Models for Multichannel Audio Source Separation","volume":"26","author":"Leglaive","year":"2018","journal-title":"IEEE-ACM Trans. Audio Speech"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1933","DOI":"10.1007\/s11277-019-06502-y","article-title":"Towards Security of GSM Voice Communication","volume":"108","author":"Abro","year":"2019","journal-title":"Wirel. Pers. Commun."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"110782","DOI":"10.1016\/j.chaos.2021.110782","article-title":"A new memductance-based fractional-order chaotic system and its fixed-time synchronization","volume":"145","author":"Dutta","year":"2021","journal-title":"Chaos Solitons Fract."},{"key":"ref_8","first-page":"205","article-title":"Constructive proof of Lagrange stability and sufficient\u2014Necessary conditions of Lyapunov stability for Yang-Chen chaotic system","volume":"309","author":"Liao","year":"2017","journal-title":"Appl. Math. Comput."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11128-020-02724-3","article-title":"Image encryption using quantum 3-D Baker map and generalized gray code coupled with fractional Chen\u2019s chaotic system","volume":"19","author":"Musanna","year":"2020","journal-title":"Quantum Inf. Process."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"103251","DOI":"10.1016\/j.engappai.2019.103251","article-title":"A polynomial-fuzzy-model-based synchronization methodology for the multi-scroll Chen chaotic secure communication system","volume":"87","author":"Chen","year":"2020","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.sigpro.2006.04.008","article-title":"A general contrast function based blind source separation method for convolutively mixed independent sources","volume":"87","author":"Leung","year":"2007","journal-title":"Signal Process."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1109\/TSA.2005.851925","article-title":"A frequency domain method for blind source separation of convolutive audio mixtures","volume":"13","author":"Rahbar","year":"2005","journal-title":"IEEE Trans. Audio Speech"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"106331","DOI":"10.1016\/j.ymssp.2019.106331","article-title":"Convolutive blind source separation in frequency domain with kurtosis maximization by modified conjugate gradient","volume":"134","author":"Cheng","year":"2019","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2580","DOI":"10.1016\/j.neucom.2010.05.018","article-title":"Convolutive blind source separation by efficient blind deconvolution and minimal filter distortion","volume":"73","author":"Zhang","year":"2010","journal-title":"Neurocomputing"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.neucom.2014.02.033","article-title":"A fast blind source separation algorithm based on the temporal structure of signals","volume":"139","author":"Zhang","year":"2014","journal-title":"Neurocomputing"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1990","DOI":"10.1016\/j.sigpro.2008.02.003","article-title":"Blind source separation for convolutive mixtures based on the joint diagonalization of power spectral density matrices","volume":"88","author":"Mei","year":"2008","journal-title":"Signal Process."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Pinchas, M. (2019). A New Efficient Expression for the Conditional Expectation of the Blind Adaptive Deconvolution Problem Valid for the Entire Range of Signal-to-Noise Ratio. Entropy, 21.","DOI":"10.3390\/e21010072"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.softx.2017.11.005","article-title":"Short-Time Fourier Transform with the Window Size Fixed in the Frequency Domain (STFT-FD): Implementation","volume":"8","author":"Mateo","year":"2018","journal-title":"Softwarex"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/0165-1684(94)90029-9","article-title":"Independent component analysis, a new concept","volume":"36","author":"Comon","year":"1994","journal-title":"Signal Process."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Hyvarinen, A., Karhunen, J., and Oja, E. (2001). Independent Component Analysis, John Wiley Sons.","DOI":"10.1002\/0471221317"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.dsp.2019.01.022","article-title":"Underdetermined convolutive blind separation of sources integrating tensor factorization and expectation maximization","volume":"87","author":"Xie","year":"2019","journal-title":"Digit. Signal Process."},{"key":"ref_22","first-page":"1","article-title":"A survey of convolutive blind source separation methods","volume":"8","author":"Pedersen","year":"2007","journal-title":"Spring Handb. Speech Process. Commun."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0925-2312(00)00345-3","article-title":"An approach to blind source separation based on temporal structure of speech signals","volume":"41","author":"Murata","year":"1998","journal-title":"Neurocomputing"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Kim, T., Lee, I., and Lee, T.W. (November, January 29). Independent vector analysis: Definition and algorithms. Proceedings of the 2006 Fortieth Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA.","DOI":"10.1109\/ACSSC.2006.354986"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1109\/TASL.2006.872618","article-title":"Blind source separation exploiting higher-order frequency dependencies","volume":"15","author":"Kim","year":"2007","journal-title":"IEEE Trans. Audio Speech"},{"key":"ref_26","unstructured":"Waqas, R., Syed, M.N., and Jonathon, A.C. (2016, January 10\u201313). Mixed Source Prior for the Fast Independent Vector Analysis Algorithm. Proceedings of the 2016 9th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2016), Rio de Janeiro, Brazil."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1859","DOI":"10.1016\/j.sigpro.2007.01.010","article-title":"Fast fifixed-point independent vector analysis algorithms for convolutive blind source separation","volume":"87","author":"Lee","year":"2007","journal-title":"Signal Process."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1431","DOI":"10.1109\/TCSI.2010.2048777","article-title":"Real-Time Independent Vector Analysis for Convolutive Blind Source Separation","volume":"57","author":"Kim","year":"2010","journal-title":"IEEE Trans. Circuits Syst. I"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1672","DOI":"10.1109\/TSP.2011.2181836","article-title":"Joint Blind Source Separation With Multivariate Gaussian Model: Algorithms and Performance Analysis","volume":"60","author":"Anderson","year":"2012","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Liang, Y., Naqvi, S.M., and Chambers, J.A. (2012). Audio video based fast fixed-point independent vector analysis for multisource separation in a room environment. EURASIP J. Adv. Signal Process., 183.","DOI":"10.1186\/1687-6180-2012-183"},{"key":"ref_31","first-page":"3","article-title":"Yet Another Chaotic Attractor","volume":"73","author":"Chen","year":"1999","journal-title":"Int. J. Bifurc. Chaos"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1142\/S0218127402004735","article-title":"The compound structure of Chen\u2019s attractor","volume":"12","author":"Zhou","year":"2002","journal-title":"Int. J. Bifurc. Chaos"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Wang, P., Li, J., and Zhang, H. (2018). Decoupled Independent Vector Analysis Algorithm for Convolutive Blind Source Separation without Orthogonality Constraint on the Demixing Matrices. Math. Probl. Eng., 2018.","DOI":"10.1155\/2018\/9868725"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Hershey, J.R., and Olsen, P.A. (2007, January 15\u201320). Approximating the Kullback Leibler divergence between Gaussian mixture models. Proceedings of the 2007 IEEE International Conference on Acoustics, Speech and Signal Processing-ICASSP, Honolulu, HI, USA.","DOI":"10.1109\/ICASSP.2007.366913"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1016\/j.laa.2017.06.012","article-title":"The Hessian matrix of Lagrange function","volume":"531","author":"Chen","year":"2017","journal-title":"Linear Algebra Appl."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1462","DOI":"10.1109\/TSA.2005.858005","article-title":"Performance measurement in blind audio source separation","volume":"14","author":"Vincent","year":"2006","journal-title":"IEEE Trans. Audio Speech"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1928","DOI":"10.1016\/j.sigpro.2011.10.007","article-title":"The signal separation evaluation campaign (2007\u20132010): Achievements and remaining challenges","volume":"92","author":"Vincent","year":"2012","journal-title":"Signal Process."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.1109\/TNN.2006.875991","article-title":"Efficient variant of algorithm FastICA for independent component analysis attaining the Cramer-Rao lower bound","volume":"17","author":"Koldovsky","year":"2006","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_39","first-page":"360","article-title":"Algorithm to eliminate permutation of frequency domain blind source separation based on influence factor","volume":"42","author":"Bo","year":"2014","journal-title":"Acta Electron. Sin."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"106657","DOI":"10.1016\/j.compeleceng.2020.106657","article-title":"Speech enhancement\u2014An enhanced principal component analysis (EPCA) filter approach","volume":"85","author":"Srinivasarao","year":"2020","journal-title":"Comput. Electr. Eng."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.csl.2003.12.001","article-title":"Measuring speech quality for text-to-speech systems: Development and assessment of a modified mean opinion score (MOS) scale","volume":"19","author":"Mahesh","year":"2005","journal-title":"Comput. Speech Lang."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.specom.2017.06.007","article-title":"A permutation algorithm based on dynamic time warping in speech frequency-domain blind source separation","volume":"92","author":"Lv","year":"2017","journal-title":"Speech Commun."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.specom.2019.11.002","article-title":"A low-complexity permutation alignment method for frequency-domain blind source separation","volume":"115","author":"Fang","year":"2019","journal-title":"Speech Commun."}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/14\/6\/165\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:08:16Z","timestamp":1760162896000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/14\/6\/165"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,26]]},"references-count":43,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["a14060165"],"URL":"https:\/\/doi.org\/10.3390\/a14060165","relation":{},"ISSN":["1999-4893"],"issn-type":[{"type":"electronic","value":"1999-4893"}],"subject":[],"published":{"date-parts":[[2021,5,26]]}}}