In this paper, we proposed the design method of artificial neural networks using VHDL and implement in FPGA. VHDL is a programming language that has been designed and optimized for describing the behavior of digital systems. Back propagation algorithm for the design of a neuron is described. Back propagation is popular training algorithms for multilayer perceptrons. Over the last years many imp...

Due to the rapid expansion and advancements of computer network, security has become a vital issue for modern computer network. The network intrusion detection systems play the vital role in protecting the computer networks. So, it has become a significant research issue. In spite of notable progress in intrusion detection system, there are still many opportunities to improve the existing syste...

Continuous pharmaceutical manufacturing together with PAT (Process Analytical Technology) provides a suitable platform for automatic control of the end product quality as desired by QbD (quality by design)-based efficient manufacturing. The precise control of the quality of the pharmaceutical product requires corrective actions in the process/raw material variability before product quality can ...

Wireless communication networks offer subscribers the possibilities of free mobility and access to information anywhere at any time. Therefore, electromagnetic coverage calculations are important for wireless mobile communication systems, especially in Wireless Local Area Networks (WLANs). Before any propagation computation is performed, modeling of indoor radio wave propagation needs accurate ...

This study investigated the impact of missing data in the evaluation of artificial neural network (ANN) models trained on complete data for the task of predicting whether breast lesions are benign or malignant from their mammographic Breast Imaging and Reporting Data System (BI-RADS) descriptors. A feed-forward, back-propagation ANN was tested with three methods for estimating the missing value...

A feed forward neural network (FFNN) has been trained to discriminate between power transformer magnetizing inrush and fault currents. The training algorithm used was back-propagation, assuming initially a sigmoid transfer function for the network’s processing units (“neurons”). Once the network was trained the units’ transfer function was changed to hard limiters with thresholds equal to the b...

This article presents findings concerned with the use of neural networks in the identification of deceptive behaviour. A game designed by psychologists and criminologists was used for the generation of data used to test the appropriateness of different AI techniques in the quest for counter-terrorism. A feed forward back propagation network was developed and subsequent neural network experiment...

In this paper a novel technique is proposed to design Bowtie using Artificial Neural Networks (ANN). ANN models are developed to calculate the antenna Gain for the given frequency and dimensions. ANN is designed using Feed forward back propagation neural network (FFBPNN) architecture and trained by LevenbergMarquardt training algorithm. ANN can be trained to provide the best and worst case prec...