Homayoon Beigi, Fundamentals of Speaker Recognition, Springer, New York, 2009, ISBN: 978-0-387-77591-3.

Homayoon S.M. Beigi, ``Pre-Processing the Dynamics of On-Line Handwriting Data, Feature Extraction and Recognition,'' Progress in Handwriting Recognition, A.C. Downton and S. Impedovo (eds.), World Scientific Publishers, New Jersey, 1997, pp. 191-198.

T. Fujisaki, H.S.M. Beigi, C.C. Tappert, M. Ukelson, and C.G. Wolf, ``Online Recognition of Unconstrained Handprinting: A Stroke-based System and Its Evaluation,'' From Pixels to Features III: Frontiers in Handwriting Recognition, S. Impedovo and J.C. Simon (eds.), Elsevier Science Publishers, B.V., 1992, pp.297-312.

Homayoon S.M. Beigi, ``Neural Network Learning and Learning Control Through Optimization Techniques,'' Doctoral Thesis, School of Engineering and Applied Science, Columbia University, New York City, New York, 1991.

Homayoon S.M. Beigi, ``Updating Procedures for Iterative Learning Control in Hilbert Space,'' , Invited Paper, Intelligent Automation and Soft Computing Journal (Special Issue on Learning and Repetitive Control), Vol. 8, No. 2, 2002.

Mahesh Viswanathan, Homayoon S.M. Beigi, Satya Dharanipragada, Fereydoun Maali, and Alain Tritschler, ``Multimedia Document Retrieval Using Speech and Speaker Recognition,'' Invited Paper, International Journal on Document Analysis and Recognition, IJDAR, Vol. 2, No. 4, pp. 147-162, June 20, 2000.

Homayoon S.M. Beigi, ``Adaptive and Learning-Adaptive Control Techniques based on an Extension of the Generalized Secant Method,'' Intelligent Automation and Soft Computing Journal, Vol. 3, No. 2, 1997, pp. 171-184.

	Homayoon S.M. Beigi and C. James Li ``Learning Algorithms for Feedforward Neural Networks Based on Classical and Initial-Scaling Quasi-Newton Methods,'' ISMM Journal of Microcomputer Applications, Vol. 14, No. 2, 1995, pp. 41-52.

C. James Li, Homayoon S.M. Beigi, Shengyi Li, Jiancheng Liang, ``Nonlinear Piezo-Actuator Control by Learning Self-Tuning Regulator,'' ASME Transactions, Journal of Dynamic Systems, Measurement, and Control, Vol. 115, No.4, December 1993, pp. 720-723.

Homayoon S.M. Beigi and C. James Li ``Learning Algorithms for Neural Networks Based on Quasi-Newton Methods with Self-Scaling,'' ASME Transactions, Journal of Dynamic Systems, Measurement, and Control, Vol. 115, No.1, March 1993, pp. 38-43.

Ferdinand Freudenstein, Homayoon S. Mohammad Beigi, ``On a Computationally Efficient Microcomputer Kinematic Analysis of the Basic Linkage Mechanisms,'' Invited Paper Journal of Mechanism and Machine Theory, England, Vol. 21, No. 6, 1986, pp. 467-472.