A piecewise linear neural network (PLNN) is discussed which maps N-dimensional input vectors into Mdimensional output vectors. A convergent algorithm for designing the PLNN from training data is described. The design algorithm is based on a variation of backtracking algorithm known as the ‘branch and bound’ method. The performance of the PLNN is compared with that of a multilayer perceptron (ML...

We suggest to apply the hybrid neural network based on multi layer perceptron (MLP) and adaptive resonance theory (ART-2) for solving of navigation task of mobile robots. This approach provides semi supervised learning in unknown environment with incremental learning inherent to ART and capability of adaptation to transformation of images inherent to MLP. Proposed approach is evaluated in exper...

The simplest water diversion method in irrigation systems is using intakes. Measuring the mean velocity is one of the essential hydraulic parameters in increasing the efficiency of the intake. In this study, the mean velocity was predicted for different width ratios of an intake using ANN-MLP neural network model. In order to do that, the flow field within a 90-degree intake was first simulated...

This paper describes a study of the use of four different neural network techniques for automatic speech recognition (ASR) using two common, real-world application databases. The neural network techniques investigated were the Multi-Layer Perceptron (MLP), the Multi-Output-Layer Perceptron (MOLP), which is an improved version of the MLP , the Time-Delay Neural Network (TDNN) and the Kohohnen Se...

Automatic classification of modulation schemes is of interest for both civilian and military applications. This report describes an experiment classifying six modulation schemes using a Multi-Layered Perceptron (MLP) neural network. Six key features were extracted from the signals and used as inputs to the MLP. The approach was similar to that of Azzouz and Nandi [2]. The aim was to see how the...

Network in network (NiN) is an effective instance and an important extension of deep convolutional neural network consisting of alternating convolutional layers and pooling layers. Instead of using a linear filter for convolution, NiN utilizes shallow multilayer perceptron (MLP), a nonlinear function, to replace the linear filter. Because of the powerfulness of MLP and 1 x 1 convolutions in spa...

This paper describes a novel hand gesture recognition system intended to support natural interaction with autonomously navigating robots that guide visitors in museums and exhibition centers. The proposed system utilizes upper body part tracking and two neural network-based classifiers, one for each arm. Tracking is performed in a 9-DoF configuration space and it is facilitated by means of a pr...

Handwritten Hindi digit recognition plays an important role in eastern Arab countries especially in the courtesy amounts of Arab bank checks. In this paper, we proposed an efficient offline handwritten Hindi digits recognition system and developed using Multilayer Perceptron Neural Network (MLP). The implemented system recognizes separated handwritten Hindi digits scanned using a scanner. The s...

The control of activated sludge treatment plants depends on on-line and laboratory measurements. Even though the behavior of activated sludge is basically known, long lags and the complex characteristic of biological activity set a challenge for controlling the process. In this paper MultiLayer Perceptron (MLP) neural network is applied for modelling Chemical Oxygen Demand (COD) concentration, ...