Now showing items 41-45 of 45
Comparison of classifying the material mechanical properties by using k-Nearest Neighbor and Neural Network Backpropagation
(Science Academy, 2011-03)
This paper present a development of a system with non-destructive testing on the material to define the mechanical properties of material. The experimental and testing of the material mechanical properties using vibration ...
Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders
Feature extraction from the vocal signal plays very important role in the area of automatic detection of voice disorders. Many feature extraction algorithms have been developed in the last three decades based on acoustic ...
Automatic detection of voice disorders using self loop architecture in back propagation network
(Anna University, 2008-01-04)
Acoustic analysis is a non-invasive technique to detect the voice disorders and diagnose the vocal and voice disease. In the recent years, voice disease are increasing dramatically due to unhealthy social habits and voice ...
Diagnosis of voice disorders using band energy spectrum in wavelet domain
(Universiti Malaysia Perlis (UniMAP), 2008-03-08)
In the evolution of quality of speech, acoustic analyses of normal and pathological voices have become increasingly interesting to researchers in laryngology and speech pathologies. Vocal signal information plays an important ...
Probabilistic neural network based olfactory classification for household burning in early fire detection application
Determination of burning smell is important because it can help in early fire detection and prevention. In this paper, a household burning smell classification system for early fire detection application has been proposed ...