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The encryption process is transferred as the underdetermined BSS problem and is treated by means of the key images to achieve decryption. By properly generating the key images and constructing the underdetermined mixing matrix, the proposed BSS technique can achieve the security. The proposed BSS with adaptive learning rates approach is implemented by the interval type-2 fuzzy cerebellar model articulation controller (T2FCMAC) and particle swarm optimization. The T2FCMAC system is a more generalized system with better learning ability to provide the adaptive learning rate of the BSS. Besides, the particle swarm optimization is utilized to enhance the performance of convergence. Computer simulation results are shown to illustrate the effectiveness of the proposed approach.<\/jats:p>","DOI":"10.3233\/ifs-151769","type":"journal-article","created":{"date-parts":[[2016,1,15]],"date-time":"2016-01-15T12:22:47Z","timestamp":1452860567000},"page":"451-460","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Blind source separation with adaptive learning rates for image encryption"],"prefix":"10.1177","volume":"30","author":[{"given":"Meng-Tze","family":"Huang","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan, R.O.C."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ching-Hung","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, National Chung Hsing University, Taichung, Taiwan, R.O.C."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chih-Min","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan, R.O.C."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2015,9,9]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1007\/978-3-540-45224-9_51","article-title":"Asymmetric triangular fuzzy sets for classification models","volume":"2773","author":"Baldwin J.F.","year":"2003","unstructured":"BaldwinJ.F. and KarakeS.B., Asymmetric triangular fuzzy sets for classification models, Lecture Notes Comp Sci 2773 (2003), 364\u2013370.","journal-title":"Lecture Notes Comp Sci"},{"issue":"3","key":"e_1_3_2_3_2","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1109\/78.489029","article-title":"General approach to blind source separation","volume":"44","author":"Cao X.R.","year":"1996","unstructured":"CaoX.R. and LiuR.W., General approach to blind source separation, IEEE Trans Signal Processing 44(3) (1996), 562\u2013571.","journal-title":"IEEE Trans Signal Processing"},{"key":"e_1_3_2_4_2","doi-asserted-by":"crossref","first-page":"3017","DOI":"10.1109\/78.553476","article-title":"Equivariant adaptive source separation","volume":"44","author":"Cardoso J.F.","year":"1996","unstructured":"CardosoJ.F. and LaheldB.H., Equivariant adaptive source separation, IEEE Trans Signal Processing 44 (1996), 3017\u20133030.","journal-title":"IEEE Trans Signal Processing"},{"key":"e_1_3_2_5_2","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/S0164-1212(01)00029-2","article-title":"A new encryption algorithm for image cryptosystems","volume":"58","author":"Chang C.C.","year":"2001","unstructured":"ChangC.C., HwangM.S. and ChenT.S., A new encryption algorithm for image cryptosystems, The Journal of Systems and Software 58 (2001), 83\u201391.","journal-title":"The Journal of Systems and Software"},{"key":"e_1_3_2_6_2","first-page":"157","article-title":"Selfadaptive neural networks for blind separation of sources","volume":"2","author":"Cichocki A.","year":"1996","unstructured":"CichockiA., AmariS., AdachiM. and KasprzakW., Selfadaptive neural networks for blind separation of sources, Proc 1996 Int Symp Circuits Syst 2 (1996), 157\u2013160.","journal-title":"Proc 1996 Int Symp Circuits Syst"},{"issue":"1","key":"e_1_3_2_7_2","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/S0925-2312(98)00091-5","article-title":"Neural networks for blind separation with unknown number of sources","volume":"24","author":"Cichocki A.","year":"1999","unstructured":"CichockiA., KarhunenJ., KasprzakW. and VigarioR., Neural networks for blind separation with unknown number of sources, Neurocomputing 24(1-3) (1999), 55\u201393.","journal-title":"Neurocomputing"},{"key":"e_1_3_2_8_2","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/0165-1684(91)90080-3","article-title":"Blind separation of source, part II: Program statement","volume":"24","author":"Comon P.","year":"1991","unstructured":"ComonP., JuttenC. and HeraultJ., Blind separation of source, part II: Program statement, Signal Processing 24 (1991), 11\u201320.","journal-title":"Signal Processing"},{"key":"e_1_3_2_9_2","unstructured":"CoverT. and ThomasJ.A. 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