Contact Info

Current Research Interests:

Pattern recognition, clustering, soft computing, data mining.

Dr. Zargham's research focuses on development of real time vector/quantization dynamical systems and adaptive decision systems. He has been able to develop an expert system for non-traditional applications such as financial market prediction. The system uses adaptation based on assignment of weights to rules. Based on past performance of a market, such a system can "learn" to provide a higher level of performance in future situations. His current work is on the development of a dynamical system for vector quantization or clustering based on ordinary differential equations (ODEs) with potential for a real-time implementation. This set of ODEs generates prototypes (or clusters) by creating valleys in its Lyapunov function. Each valley represents a cluster of similar input patterns.

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