[1] فلاح علی، کنترل تطبیقی دست سیبرنتیکی با کنترل کننده شبکه عصبی، رساله دکترا؛ دانشگاه تربیت مدرس، 1374.
[2] Hudgins B., Parker P., Scott R.N., A new strategy for multifunction myoelectric control; IEEE Trans Biomed Eng, 1993; 40(1): 82-94.
[3] Englehart K., Hudgins B., A robust, real-time control scheme for multifunction myoelectric control; IEEE Trans Biomed Eng, 2003; 50(7): 848-854.
[4] Huang Y., Englehart K.B., Hudgins B., Chan A.D.C., A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses; IEEE Trans Biomed Eng, 2005; 52(11): 1801-1811.
[5] Englehart K., Hudgins B., Chan A.D.C., Continuous multifunction myoelectric control using pattern recognition; Journal of Technology and Disability, 2003; 15(2): 95–103.
[6] Hargrove L.J., Englehart K., Hudgins B., A comparison of surface and intramuscular myoelectric signal classification; IEEE Trans Biomed Eng, 2007; 54(5): 847-853.
[7] Chan A.D.C., Green G.C., Myoelectric control development toolbox; Proc of the 30th Conf on Med and Biol Eng Society; Toronto, Canada, 2007.
[8] Englehart K., Hudgins B., Parker P.A., A wavelet-based continuous classification scheme for multifunction myoelectric control; IEEE Trans Biomed Eng, 2001; 48(3): 302-311.
[9] نظرپور کیانوش، طبقه بندی سیگنال الکترومایوگرام سطحی با استفاده از آمارگان مراتب بالا، پایاننامه کارشناسی ارشد؛ دانشگاه تربیت مدرس،؛ 1384.
[10] Clancy E.A., Hogan N., Probability density of the surface electromyogram and its relation to amplitude detectors; IEEE Trans Biomed Eng, 1999; 46(6): 730-739.
[11] نظرپور کیانوش، شرافت احمدرضا، فیروزآبادی سیدمحمد، طبقهبندی سیگنال الکترومایوگرام سطحی با استفاده از آمارگان مرتبه بالا، مجله مهندسی پزشکی زیستی، دوره اول (جدید)؛ پائیز 1386، شماره سوم، صفحات 1890-200.
[12] Nazarpour K., Sharafat A.R., Firoozabadi S.M.P.; A novel feature extraction scheme for myoelectric signals classification using higher order statistics; Proc of the 2nd Int IEEE EMBS Conf on Neural Eng, Arlington, Virginia, 2005: 5-8.
[13] Nazarpour K., Sharafat A.R., Firoozabadi S.M.P., Surface EMG signal classification using a selective mix of higher order statistics; Proc of the 27th IEEE Annual Conf on Medicine and Biology; Shanghai, China, 2005: 4208-4211.
[14] Principe J.C., Xu D., Zhao Q., Fisher J., Learning from examples with information theoretic criteria; Journal of VLSI Signal Processing-Systems, 2000; 26 (1-2): 61-77.
[15] Jenssen R., Erdogmd D., Principe J.C., Eltoft T., Towards a unification of information theoretic learning and kernel methods; IEEE Workshop on Machine Learning for Signal Processing, 2004: 93-102.
[16] Santamaría I., Pokharel P.P., Principe J.C., Generalized correlation function definition, properties, and application to blind equalization; IEEE Trans Signal Processing, 2006; 54(6): 2187-2197.
[17] Liu W., Pokharel P.P., Principe J.C., Correntropy a localized similarity measure; Proc of the Int Joint Conf on Neural Networks; Vancouver, BC, Canada, 2006: 4919-4924.
[18] Liu W., Pokharel P., Principe J., Correntropy properties and applications in non-Gaussian signal processing; IEEE Trans Signal Processing, 2007; 55(11): 5286-5298.
[19] Jeong K.H., Principe J.C., The correntropy mace filter for image recognition; Proc of the 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing; Arlington, 2006: 9-14.
[20] Li R., Liu W., Principe J.C., A unifying criterion for instantaneous blind source separation based on correntropy; Journal of Signal Processing, 2007; 1872-1881.
[21] Gunduz A., Hegde A., Principe J.C., Correntropy as a novel measure for nonlinearity tests; Proc of the Int Joint Conf on Neural Networks; Vancouver, BC, Canada, 2006: 1856-1862.
[22] Xu J.W., Pokharel P.P., Paiva A.R.C., Principe J.C., Nonlinear component analysis based on correntropy; Proc of the Int Joint Conf on Neural Networks; Vancouver, BC, Canada, 2006: 1851-1855.
[23] Pokharel P.P., Agrawal R., Principe J.C., Correntropy based matched filtering; IEEE Workshop on Machine Learning for Signal Processing, 2005: 341-346.
[24] Pokharel P.P., Xu J.W., Erdogmus D., Principe J.C., A closed form solution for a nonlinear wiener filter; Proc of the IEEE Int Conf on Acoustics, Speech and Signal Processing; Toulouse, France, 2006: 720-723.
[25] Vapnik V., The Nature of Statistical Learning Theory; Springer Verlag; New York,1995: 140-146.
[26] رمضانی محمدمهدی، شرافت احمدرضا؛ کاهش خطا در طبقهبندی بیدرنگ سیگنالهای الکترومایوگرام سطحی با استفاده از کورنتروپی؛ پانزدهمین کنفرانس مهندسی پزشکی ایران؛ دانشگاه آزاد اسلامی واحد مشهد؛ زمستان1387.