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The HCFLNN is a type of feed\u2010forward neural networks which have the ability to transform the nonlinear input space into higher dimensional\u2010space where linear separability is possible. Moreover, the proposed HCFLNN combines the best attribute of particle swarm optimization (PSO), back propagation learning (BP learning), and functional link neural networks (FLNNs). The proposed method eliminates the need of hidden layer by expanding the input patterns using Chebyshev orthogonal polynomials. We have shown its effectiveness of classifying the unknown pattern using the publicly available datasets obtained from UCI repository. The computational results are then compared with functional link neural network (FLNN) with a generic basis functions, PSO\u2010based FLNN, and EFLN. From the comparative study, we observed that the performance of the HCFLNN outperforms FLNN, PSO\u2010based FLNN, and EFLN in terms of classification accuracy.<\/jats:p>","DOI":"10.1155\/2011\/107498","type":"journal-article","created":{"date-parts":[[2011,7,27]],"date-time":"2011-07-27T19:00:20Z","timestamp":1311793220000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A Novel Learning Scheme for Chebyshev Functional Link Neural Networks"],"prefix":"10.1155","volume":"2011","author":[{"given":"Satchidananda","family":"Dehuri","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2011,7,27]]},"reference":[{"key":"e_1_2_6_1_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065792000255"},{"volume-title":"Neural Networks: A Comprehensive Foundation","year":"1999","author":"Haykin S.","key":"e_1_2_6_2_2"},{"key":"e_1_2_6_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2005188"},{"key":"e_1_2_6_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/0893-6080(91)90009-T"},{"key":"e_1_2_6_5_2","doi-asserted-by":"publisher","DOI":"10.1364\/AO.26.004972"},{"volume-title":"Adaptive Pattern Recognition and Neural Network","year":"1989","author":"Pao Y. 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