Artificial Neural Network is widely used to learn data from systems for different types of applications. The capability of different types of Integrated Circuit (IC) based ANN structures also depends on the hardware backbone used for their implementation. In this work, Field Programmable Gate Array (FPGA) based Multilayer Perceptron Artificial Neural Network (MLP-ANN) neuron is developed. Exper...

Sensor technology has been used in water environment, which comes into being a water environment wireless sensor monitoring network. Monitoring data in the network slowly change, so we propose a geographical energy-efficient multi-hop clustering fusion routing algorithm based on multilayer perceptron (MLP-GEEMHCFR) in this paper to reduce transmittingdata and save the network energy.The algorit...

We propose Very Simple Classifier (VSC) a novel method designed to incorporate the concepts of subsampling and locality in the definition of features to be used as the input of a perceptron. The rationale is that locality theoretically guarantees a bound on the generalization error. Each feature in VSC is a maxmargin classifier built on randomly-selected pairs of samples. The locality in VSC is...

In this paper, we propose an approach for Stress Assignment in Spanish Proper Names, based on a Multi-Layer Perceptron (MLP). When assigning stress to a word, we first analyse each vowel in the word and then calculate a Stress-Confidence Measure for it, using a MLP. The system will assign the stress to the vowel with the highest stress-confidence measure. In this paper we present and analyse di...

Password authentication is the most commonly used identification system in today’s computer world. Its security can be enhanced using typing biometrics as a transparent layer of user authentication. Our research focuses on using the time period between keystrokes as the measure of the individual’s typing pattern. The typing pattern of a particular individual can be represented by the weights of...

Snoring detection is important for diagnosing obstructive sleep apnea syndrome (OSAS) and other respiratory sleep disorders. In general, audio signal processing such as snoring sound analysis uses the frequency characteristics of the signal. Recently, a correlational filter Multilayer Perceptron neural network (f-MLP) has been proposed, which has the first hidden layer of correlational filter o...

The Fake News Challenge (FNC-1) is a public competition that aims to find automatic methods for detecting fake news. The dataset for the challenge consists of headline-body pairs, with the objective being to classify the pairs as unrelated, agreeing, disagreeing, or discussing. We developed four neural network models for FNC-1, two using a feed-forward architecture and two using a recurrent arc...

In this paper, we propose a new method of phoneme segmentation using MLP(multi-layer perceptron). The structure of the proposed segmenter consists of three parts: preprocessor, MLP-based phoneme segmenter, and postprocessor. The preprocessor utilizes a sequence of 44 order feature parameters for each frame of speech, based on the acoustic-phonetic knowledge. The MLP has one hidden layer and an ...

Abstract—A glia is a nervous cell in the brain. Currently, the glia is known as a important cell for the human’s cerebration. Because the glia transmits signals to neurons and other glias. We notice features of the glia and consider to apply it for an artificial neural network. In this paper, we propose a Multi-layer perceptron (MLP) with pulse glial chain. The pulse glial chain is inspired fro...

Classification of banded metaphase chromosomes is an important step io automated clinical chromosome analysis. We have conducted a preliminary investigation of the application of aaificial neural networks to this process, making use of a natural representation of the banding pattern. Two different network architectures have been compared the Kohonen %IF-organizing feature map and the multi-laye...