In this paper a noise robust feature extraction algorithm using joint wavelet packet decomposition (WPD) and an autoregressive (AR) modeling of the speech signal is presented. In opposition to the short time Fourier transform (STFT) based time-frequency signal representation, a computationally efficient WPD can lead to better representation of non-stationary parts of the speech signal (consonan...

Speech is a natural mode of communication for people and speech recognition is an intensive area of research due to its versatile applications. This paper presents a comparative study of various feature extraction methods based on wavelets for recognizing isolated spoken words. Isolated words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition....

A novel speech enhancement system based on wavelet packet decomposition (WPD) is proposed. Noise level is estimated based on quantile in wavelet threshold domain. To handle colored and non-stationary noises, the universal thresholds are weighted by a time-frequency dependent nonlinear function. Two nonlinear weighting methods using temporal threshold variation and kernel smoothing are proposed....

Accurate precipitation prediction can help plan for different water resources management demands and provide an extension of lead-time the tactical strategic planning courses action. This paper examines applicability several forecasting models based on wavelet packet decomposition (WPD) in annual rainfall forecasting, a novel hybrid framework (WPD-ELM) is proposed coupling extreme learning mach...

This paper presents a statistical learning algorithm based on Support Vector Machines (SVMs) for the classification of Malayalam Consonant – Vowel (CV) speech unit in noisy environments. We extend SVM for multiclass classification using Decision Directed Acyclic Graph Support Vector Machine (DDAGSVM) algorithm. For classification, acoustical features are extracted using Wavelet Transform (WT) b...

Impact acoustic is an effective non-destructive evaluation (NDE) method for many applications especially for inspecting the bonding quality of mosaic tile-walls. However, the audio noise can affect the power spectrum density (PSD) distribution of an acquired signal seriously. So, the traditional method of using PSD as the main identification tool is not sufficient. This paper proposes an evalua...

Abstract This paper proposes a hybrid deep reinforcement learning framework for locomotive axle temperature by combining the wavelet packet decomposition (WPD), long short-term memory (LSTM), gated recurrent unit (GRU) and generalized autoregressive conditional heteroskedasticity (GARCH) algorithms. The WPD is utilized to decompose raw nonlinear series into subseries. Then predictors LSTM GRU a...

In this paper, a fault protection diagnostic scheme for power distribution system is proposed. The comprises wavelet packet decomposition (WPD) signal processing and analysis support vector machine (SMV) classification location. tested on reduced Eskom 132 kV line. WPD used to extract signatures of interest the SVM subsequently locating various conditions. Furthermore, we investigate effectiven...

The electrocardiogram (ECG) is one of the most important techniques for heart disease diagnosis. Many traditional methodologies of feature extraction and classification have been widely applied to ECG analysis. However, the effectiveness and efficiency of such methodologies remain to be improved, and much existing research did not consider the separation of training and testing samples from the...