Wavelet applications in medicine
IEEE Spectrum
Iterated wavelet transformation and signal discrimination for HRR radar target recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Expert Systems with Applications: An International Journal
The speaker identification by using genetic wavelet adaptive network based fuzzy inference system
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An intelligent system using adaptive wavelet entropy for automatic analog modulation identification
Digital Signal Processing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An automatic diabetes diagnosis system based on LDA-Wavelet Support Vector Machine Classifier
Expert Systems with Applications: An International Journal
A New Expert System for Diagnosis of Lung Cancer: GDA--LS_SVM
Journal of Medical Systems
Hybrid adaptive wavelet-neuro-fuzzy system for chaotic time series identification
Information Sciences: an International Journal
A new method for expert target recognition system: Genetic wavelet extreme learning machine (GAWELM)
Expert Systems with Applications: An International Journal
Automatic RNA virus classification using the Entropy-ANFIS method
Digital Signal Processing
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In this paper, an intelligent target recognition system is presented for target recognition from target echo signal of High Resolution Range (HRR) radars. This paper especially deals with combination of the feature extraction and classification from measured real target echo signal waveforms using X –band pulse radar. Because of this, a wavelet adaptive network based fuzzy inference systemmodel developed by us is used. The model consists of two layers: wavelet and adaptive network based fuzzy inference system. The wavelet layer is used for adaptive feature extraction in the time-frequency domain and is composed of wavelet decomposition and wavelet entropy. The used for classification is an adaptive network based fuzzy inference system. The performance of the developed system has been evaluated in noisy radar target echo signals. The test results showed that this system was effective in detecting real radar target echo signals. The correct classification rate was about 93% for used target subjects.