Voice Pathology Detection Using the Adaptive Orthogonal Transform Method, SVM and MLP.

In this paper, an automatic voice pathology recognition system is realized. The special features are extracted by the Adaptive Orthogonal Transform method, and to provide their statistical properties we calculated the average, variance, skewness and kurtosis values. The classification process uses two models that are widely used as a classification method in the field of signal processing: Support Vector Machine (SVM) and Multilayer Perceptron (MLP). The proposed system is tested by using a German voice database: the Saarbruecken Voice Database (SVD). The experimental results show that the Adaptive Orthogonal Transform method works perfectly with the Multilayer Perceptron Neural Network, which achieved 98.87% accuracy. On the other hand, the combination of the Adaptive Orthogonal Transform method and Support Vector Machine reached 85.79% accuracy.

Generalized Orthogonal Discrete W Transform and Its Fast Algorithm

Based on the generalized discrete Fourier transform, the generalized orthogonal discrete W transform and its fast algorithm are proposed and derived in this paper. The orthogonal discrete W transform proposed by Zhongde Wang has only four types. However, the generalized orthogonal discrete W transform proposed by us has infinite types and subsumes a family of symmetric transforms. The generalized orthogonal discrete W transform is a real-valued orthogonal transform, and the real-valued orthogonal transform of a real sequence has the advantages of simple operation and facilitated transmission and storage. The generalized orthogonal discrete W transforms provide more basis functions with new frequencies and phases and hence lead to more powerful analysis and processing tools for communication, signal processing, and numerical computing.

Development of Quantum Hartley Transform for Signal Processing Applications

The present paper deals with the q-analogue of Hartley transform which is the q-extension of Hartley transform. It is an orthogonal transform which is defined in the domain -∞ to ∞ whose kernel is (cosinusidal) function ‘cas’ which is a combination of trigonometrical functions ‘sin’ and ‘cos’. The q-analogue of Hartley transform is defined in the domain -∞ to ∞ whose kernel is ‘cas_q’ function which is a q-extension of ‘cas’ function. In the similar manner ‘cas_q’ is a q-extension of combination of q-extension of trigonometrical functions ‘sin_q’ and ‘cos_q’ defined in Kack and Chengue book [18]. In this paper we will establish some basic properties of q-Hartley transform, for instance linear property, change of scale property.