Zhong ZHANG †

Profile †

Zhong ZHANG is a professor of the Production Systems Engineering department at Toyohashi University of Technology. He received his Bachelor engineering, Master engineering degrees in 1982 and 1984, respectively, from Xi'an Highway University, China and his Doctor engineering degree in 1993 from Okayama University, Japan. He was a visiting scholar at the University of Melbourne, Australia in 1998. He engaged in researches regarding intelligent system and signal, Image processing as a senior researcher at the Industrial Technology Center of Okayama Prefecture, an associate professor at Okayama Prefecture University, and now a professor at instrumentation systems Laboratory of Toyohashi University of Technology.

Members of the Japan Mechanical Engineers; the Society of Instrument and control Engineers, Japan; Society of Automotive Engineers of Japan; Research Institute of Signal Processing, Japan; Institute of Electrical Engineers of Japan; IEEE.

Research †

The development of instrumentation systems consisting mainly of intellectual state evaluation, pursuit, prediction, and diagnostic technology based on measurement engineering and intellectual systems engineering is the main objective of my research. The research theme is set up by making "human and system" into a keyword, and aims to establish technology gentle to people. The main research themes are as follows:

1. Research on the wavelet transform
   1. Construction of complex discrete wavelet transforms
   2. The design of real mother wavelets and their filter banks
   3. Development of signal and image processing methods using the wavelet transform
   4. Development of fusion technologies of the wavelet transform and circumferential technologies (fractal, chaos, neural network, etc.)
2. Research on cellar neural networks (CNN)
   1. The optimal design of the CNN as an associative memory
   2. Development of the intellectual sensor using the CNN
   3. Filtering and image processing with the CNN
3. Research on intellectual state evaluation, diagnosis, and prediction technology
   1. Intellectual abnormal diagnosis with neural networks
   2. Feature extraction and pattern recognition using self-organization maps
   3. State change pursuit and prediction of systems using chaos analysis
   4. Evaluation and prediction technologies using fractal analysis
4. Research on reduction technologies of vibration, noise and acoustic design
   1. Intellectual Acquiring Localization of 3-dimensional sound sources
   2. Separation of sound sources by independent component analysis (ICA)
   3. Sound design of the machine systems and sound synthesis
   4. Quantitative evaluation of comfortable and unpleasant sound signals by correlation analysis of sounds and brain waves

Bibliography? †