The training algorithm of Wavelet Neural Networks (WNN) is a bottleneck which impacts on the accuracy of the final WNN model. Several methods have been proposed for training the WNNs. From the perspective of our research, most of these algorithms are iterative and need to adjust all the parameters of WNN. This paper proposes a one-step learning method which changes the weights between hidden la...

A simple algorithm is presented for evaluating scattering parameters of a two-port network. This technique uses the indefinite admittance matrix to calculate scattering or any other desired set of two-port parameters.

Abstract- Communication has become inevitably part of our day to day activities, in academic, business, banking, and other sectors. It has therefore become so important to implement good and efficient communication system. A reference point according to this research is the wireless sensor networking (WSN) system, and most important thing in communication is to be free from interference, attenu...

investigation of soil properties like cation exchange capacity (cec) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. pedotransfer functions (ptfs) provide an alternative by estimating soil parameters from more readily available soil data...

production of highly viscous tar sand bitumen using steam assisted gravity drainage (sagd) with a pair of horizontal wells has advantages over conventional steam flooding. this paper explores the use of artificial neural networks (anns) as an alternative to the traditional sagd simulation approach. feed forward, multi-layered neural network meta-models are trained through the back-error-propaga...

in this paper, the temperature distribution in workpiece and microstructure of welded zone in friction stir welding of aluminum 1100 alloys and the effect of the tool rotational speed on these parameters have investigated experimentally. also feed forward back propagation neural network has been used to predict the temperature of the workpiece during the welding process by considering the proce...

From speech, speaker identity can be mostly characterized by the spectro-temporal structures of spectrum. Although recent researches have demonstrated the effectiveness of employing long short-term memory (LSTM) recurrent neural network (RNN) in voice conversion, traditional LSTM-RNN based approaches usually focus on temporal evolutions of speech features only. In this paper, we improve the con...

Abstract—Vector network analyzer (VNA) is versatile measuring equipment which is primarily used for two-port device S parameters measurements. This paper addresses measurement of capacitor parameters using VNA in broad frequency range. The main attention is focused on the measurement accuracy of capacitors parameters using VNA and proper de-embedding of an experimental setup parasitics to get a...

Introduction An n-port resistive network is an n-port circuit consisting of only passive resistors, which is an important class of passive networks. An n-port resistive network is usually characterized by its impedance or admittance matrix. Since there are no reactive elements, passivity and reciprocity imply that the impedance and admittance matrices of n-port resistive networks must be nonneg...