(*) Summary. Particle filter is a technique for implementing recursive Bayesian filter by Monte Carlo simulation. It becomes one of the most popular methods for stochastic dynamic estimation problems. Practical applications include estimation, tracking, and information fusion among others. Key ideas will be presented and results of implemented practical example will be given. Disadvantages of particle filter implementation will be discussed.

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(**) Biodata: Prof. Dr. Imbaby I. Mahmoud is a Prof. of Computer and System Engineering at the Engineering Dept., NRC, Atomic Energy Authority, Cairo, Egypt. He was appointed as demonstrator in the same Department in 1983.
He earned his Dr. Eng. Degree from School of Science and Engineering, Waseda University, Tokyo, Japan in March 1994 in the field of VLSI Design.
He worked at the KFKI, Hungarian Academy of Sciences, Budapest, Hungary in CPLD design for reactor control under IAEA fellowship from May to August 1998. Also he served as technical officer of IAEA TC Project EGY/043 entitled Environmental Monitoring Instruments from 1999-2001.
During the period Oct. 2001-Jun2007 Prof. Imbaby was teaching programming, computer logic, computer networks and graduation projects at Dammam College of Technology, Dammam, Saudi Arabia. In the same period he was supervising M. Sc. and Ph. D. candidates in Egypt in the field of design and implementation of different algorithms in FPGA.
Prof. Imbaby is a member of the following scientific societies:
- Member of IEICE (The Institute of Electronics, Information and Communication Engineers, EIC) -1990:1994 - Japan,
- IEEE (Computer society affiliate) -1994 - USA,
- Engineers syndicate of Egypt - Egypt, and
- Egyptian Society of Nuclear Sciences and Applications (ESNSA) - Egypt.

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(***) From work by H. A. Abd El-Halym , Imbaby I. Mahmoud, and S. E.-D. Habib.