This paper proposes a novel approach for an optimal multi-objective optimization for VLSI implementation of Artificial Neural Network (ANN) which is area-power-speed efficient and has high degree of accuracy and dynamic range. A VLSI implementation of feed forward neural network in floating point arithmetic IEEE-754 single precision 32 bit format is presented that makes the use of digital weigh...

In this work, a channel estimation technique based on Artificial Neural Networks (ANN) has been proposed as an alternative to pilot based channel estimation technique for Space-Time Block Coded Multiple-Input Multiple-Output (STBCMIMO) systems over Rayleigh fading channels. ANNs, due to their high degree of adaptability, can be used for modelling the nonlinear phenomenon of channel estimation a...

In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and t...

The research presented in this paper is based on the artificial neural networks recognition paradigm applied to Romanian isolated word recognition. The network, which is composed by three layer (a Multilayer Perceptron), is trained by conventional Back-propagation algorithm. The ANN speech recognition system based on Mel Frequency Cepstral Coefficients was developed using Matlab toolkit. The sy...

In this paper, a closed-loop, smart transducer design is proposed, based on artificial neural network (ANN) techniques. The design aims to improve the performance of open-loop, off-the-shelf capacitive acceleration sensors and increase their robustness to manufacturing tolerances. A Òmodel referenceÓ control strategy was adopted for the design of the smart transducer. Multilayer perceptron (MLP...

In this paper, learning algorithm for a multiplicative neural network motivated by spiking neuron model (MSN) is proposed and tested for various applications where a multilayer perceptron (MLP) neural network is conventionally used. It is observed that the inclusion of a few more biological phenomena in the formulation of artificial neural network models make them more prevailing. Several bench...

The approach to the design of direct current (DC) motor varies considerably using advanced methods such as artificial intelligence (AI). However, accuracy issues cannot be totally addressed using conventional methods. This paper presents the study on nonlinear autoregressive moving average with exogenous input (NARMAX) model using multilayer perceptron (MLP) neural network for DC motor modeling...

introductapplication of neural network of multi layers perceptron (mlp) in site selection of municipal solid ‎waste landfilling with emphasis on hydrogeomorphic characteristics (case study: fereydoonshahr city)‎introduction‏:‏cities are at the nexus of a further threat to the environment, namely the production of an increasing ‎quantity and complexity of wastes. the estimated quantity of munici...

Bio-absorbent palm fiber was applied for removal of cationic violet methyl dye from water solution. For this purpose, a solid phase extraction method combined with the artificial neural network (ANN) was used for preconcentration and determination of removal level of violet methyl dye. This method is influenced by factors such as pH, the contact time, the rotation speed, and the adsorbent dosag...