Boltzmann mach ine neural network bas been used to recognize the Arabic speech.  Fast Fourier transl(>lmation algorithm has been used t() extract speciral 'features from an a caustic signal .

The  spectral  feature size is reduced by series of operations in

order to make it salable as input for a neural network which is used as a recogni zer by Boltzmann Machine Neural  network which has been used as a recognizer for phonemes . A training set consist of a number of Arabic phoneme repesentations, is used to train lhe neuntl network.

The neural network recognized Arabic. After Boltzmann Machine Neura l    network   training  the  system   with 

In this study water quality was indicated in terms of Water Quality Index that was determined through summarizing multiple parameters of water test results. This index offers a useful representation of the overall quality of water for public or any intended use as well as indicating pollution, water quality management and decision making. The application of Water Quality Index (WQI) with sixteen physicochemical water quality parameters was performed to evaluate the quality of Tigris River water for drinking usage. This was done by subjecting the water samples collected from eight stations in Baghdad city during the period 2004-2010 to comprehensive physicochemical analysis. The sixteen physicochemical parameters included: Turbidity,

In this study water quality was indicated in terms of Water Quality Index that was determined through summarizing multiple parameters of water test results. This index offers a useful representation of the overall quality of water for public or any intended use as well as indicating pollution, water quality management and decision making. The application of Water Quality Index
(WQI) with sixteen physicochemical water quality parameters was performed to evaluate the quality of Tigris River water for drinking usage. This was done by subjecting the water samples collected from eight stations in Baghdad city during the period 2004-2010 to comprehensive physicochemical analysis. The sixteen physicochemical parameters included: Turbidity, A

Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per