Individual component reliability can often be estimated from degradation signals. In this paper, we examine the utility of the wavelet transform in pre-processing degradation signals for on-line reliability estimation. Wavelet preprocessing facilitates examination of degradation signals in both the timeand frequency-domains, simultaneously. Neural networks are used for forecasting the degradati...

With progress in radar systems, a number of methods have been developed for signal processing and detection in radars. A number of modern radar signal processing methods use time-frequency transforms, especially the wavelet transform (WT) which is a well-known linear transform. The interference canceling is one of the most important applications of the wavelet transform. In Ad-hoc detection met...

This research presents the multi –modal biometric system for iris and fingerprint This paper presents the Feature level fusion using wavelet for combining two unimodal biometric system. Gabor transform is used for feature extraction and wavelet transformation for fusion of iris and fingerprint. The system applied artificial neural network technique for recognizing whether the user is genuine (a...

Speech impairments are one of the earliest manifestations in patients with Parkinson’s disease. Particularly, articulation deficits related to the capability of the speaker to start/stop the vibration of the vocal folds have been observed in the patients. Those difficulties can be assessed by modeling the transitions between voiced and unvoiced segments from speech. A robust strategy to model t...

this paper deals with the classification of cardiovascular disease for its future analysis. If future progression of the disease can be predicted earlier with proper change in medication patients treatment can be improved. Artificial neural network (ANN) is used as classifier with wavelet transform as the feature extraction for reducing data set of ECG. Hidden markov model (HMM) is used as pred...

With progress in radar systems, a number of methods have been developed for signal processing and detection in radars. A number of modern radar signal processing methods use time-frequency transforms, especially the wavelet transform (WT) which is a well-known linear transform. The interference canceling is one of the most important applications of the wavelet transform. In Ad-hoc detection met...

In this paper, a new method based on artificial neural network (ANN) and discrete wavelet transform (DWT) is proposed for electrical islanding detection. Transient signals produced during an event are used in the proposed method. ANN is trained to classify the transient events as islanding and nonislanding. The required features for classifying are extracted through DWT of voltage and current t...

In this paper, we present an edge detection method based on wavelet transform and Hessian matrix of image at each pixel. Many methods which based on wavelet transform, use wavelet transform to approximate the gradient of image and detect edges by searching the modulus maximum of gradient vectors. In our scheme, we use wavelet transform to approximate Hessian matrix of image at each pixel, too. ...

The Discrete Wavelet Transform (DWT) is a transformation that can be used to analyze the temporal and spectral properties of non-stationary signals. In this paper we describe some applications of the DWT to the problem of extracting information from normal and abnormal arterial pulses. We shall review a feature extraction algorithm of pulse signals, wavelet analysis, with aim of generating the ...