Deep learning is an emerging area in current scenario. Mostly, Convolutional Neural Network (CNN) and Deep Belief Network (DBN) are used as the model in deep learning. It is termed as Deep Neural Network (DNN). The use of DNN is widely spread in many applications, exclusively for detection and classification purpose. In this paper, authors have used the same network for signal enhancement purpose. Speech is considered for the input signal with noise. The model of DNN is used with two layers. It has been compared with the ADALINE model to prove its efficacy.
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There is an increase in cardio logical patients all over the world due to change in modern life style. It forces the medical researchers to search for smart devices that can diagnosis and predict the onset of cardiac problem before it is too late. This motivates the authors to predict Arrhythmia that can help both the patients and the medical practitioners for better healthcare services. The proposed method uses the frequency domain information which can represent the ECG signals of Arrhythmia patients better. Features representing the MIT-BIH Arrhythmia are extracted using the efficient Short Time Fourier Transform and the Wavelet transform. A comparison of these features is made with that of normal human being using Neural Network based classifier. Wavelet based features has shown an improvement of Accuracy over that of STFT features in classifying Arrhythmia as our results reveal. A Mean Square Error (MSE) of with wavelet transform has validated our results.
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The necessity of clean environment is the major aspect in this modern age. This maintains a healthy environment. Also several trials have made with multidisciplinary researchers for development of healthy environment. However, it is even important to facilitate the unhealthy people in the healthcares. Some extent technology has an important role to support it. In this paper, a case study of water supply in the modern health care units is analyzed. This work describes the application of rule based Fuzzy Logic for control operation in water supply section. To refine fuzzy rules' initial approximate set automatically, a self-organizing fuzzy controller has been used. The quality factor is increased by applying the PD-type fuzzy controller. To make the system robust, the controller has been designed with Fuzzy Logic rules. The simulation results confirm the advantages and demonstrate for better dynamic behavior and performance, as well as perfect control with no overshoot. For low energy consumption, either the energy input is decreased or the efficiency of the mechanical transmission and processes has been increased. Performance of these new controllers has been verified through simulation using MATLAB.
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