Applications, which need to store large database and/or transmit digital images requiring high bit-rates over channels with limited bandwidth, have demanded improved image compression techniques. This paper describes practical and effective image compression system based on neuro-fuzzy model which combines the advantages of fuzzy vector quantization with neural network and wavelet transform. Th...

This paper presents a novel method for automatic handwritten character recognition by combining wavelet packet transform with neurofuzzy approach. The time-frequency localization and compression capability of wavelet packet transform using best-basis algorithm is used for feature extraction, enhancing the accuracy of recognition at pixel level. The best-basis algorithm automatically adapts the ...

The main aim of this lecture is to summarize the problems associated with subband coded images quality measure and control. The attempts and suggestions for solving this problems are presented. The emphasis are on our methods, that use fuzzy logic and neural networks. Key-Words: wavelet-transform, standard image quality measures, subjective image quality

During the past several years, fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of the fuzzy set theory, especially in the realm of the industrial processes, which do not lend themselves to control by conventional methods because of a lack of quantitative data regarding the inputoutput relations i.e., accurate mathematical models. The fuzzy...

this paper presents the application of radial basis neural networks to the development of a novel method for the condition monitoring and fault diagnosis of synchronous generators. in the proposed scheme, flux linkage analysis is used to reach a decision. probabilistic neural network (pnn) and discrete wavelet transform (dwt) are used in design of fault diagnosis system. pnn as main part of thi...

The DC-DC power converters are widely used; however, the controller design for the DC-DC power converters cannot easily design if the load dynamics vary widely. This paper proposes an adaptive wavelet neural control (AWNC) system for a forward DC-DC power converter. The proposed AWNC system is composed of a neural controller and a robust controller. The neural controller uses a wavelet neural n...

In this paper, we proposed and trained a fuzzy neural network system to estimate future logistics demand. The structure of neural network in the system is similar to that of BP network, except that here the nonlinear sigmoid functions in the networks are replaced by fuzzy reasoning process and wavelet functions respectively. Moreover, the trained network system is put into practical logistics d...

In this paper a combined controller is proposed for nonlinear dynamical systems. The controller is constructed by a fuzzy wavelet network and nonlinear model predictive control. Chaotic optimization, which is fast and robust, is applied to generate optimized controlled input in nonlinear model predictive control. The ability of the fuzzy wavelet neural network and the proposed controller is sho...

there are a variety of electrocardiogram (ecg) based methods to detect myocardial infarction (mi) patients. this study used the signal averaged electrocardiogram (saecg) and its wavelet coefficient as an index to detect mi. orthogonal leads signals from 50 acute myocardial infarction (ami) and 50 healthy subjects were selected from the national metrology institute of germany (ptb diagnostic dat...

This paper presents a new method to design power system stabilizer (PSS) using fuzzy wavelet neural network (FWNN) for stability enhancement of a multi-machine power system. In the proposed approach, Wavelet Neural Network (WNN) is used to construct a well localized in both time and frequency domains consequent part for each fuzzy rule of a Takagi-Sugeno-Kang (TSK) fuzzy model. In designing the...