TACTILE SENSING SYSTEM USING ARTIFICIAL NEURAL NETWORKS

ABSTRACT
Object Identification plays an important role in various applications ranging from robotics to computer vision. Artificial neural network (ANN) is being used for in various pattern recognition applications due to the advantages of ability as well as adaptability to learn. This paper presents identification of object independent to size, position and orientation using the concept of ANN and moments. The image ....etc

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Abstract:
This paper deals with the application of artificial neural networks (ANNs) to fault detection and location in extra high voltage (EHV) transmission lines for high speed protection using terminal line data. The proposed neural fault detector and locator were trained using various sets of data available from a selected power network model and simulating different fault scenarios (fault types, fault locations, fault resistances and fault inception angles) and different power system data (source capacities, source voltages, source angles ....etc

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Artificial Neural Networks



Biological inspiration

Animals are able to react adaptively to changes in their external and internal environment, and they use their nervous system to perform these behaviours.

An appropriate model/simulation of the nervous system should be able to produce similar responses and behaviours in artificial systems.

The nervous system is build by relatively simple units, the neurons, so copying their behavior and functionality should be the soluti ....etc

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matlab code for face recognition using artificial neural networks ?

I HAVE TO TRAIN AND TEST THE NEURAL NETWORK FOR FACE RECOGNITION..
I HAVE EXTRACTED FEATURES USING PCA..
THANKS
[email protected] ....etc

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FACE RECOGNITION USING ARTIFICIAL NEURAL NETWORKS

Artificial Neural Networks commonly referred to as Neural Networks is a new branch of AI, that enabled a crude simulation of the structure of human brain electronically or in software. The inherent properties of human brain enable it to analyze complex patterns consisting of a number of elements, those individually reveal little of the total pattern, yet collectively represent easily recognizable objects.

The concep ....etc

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We begin by considering an Artificial neural n/w architecture in which every node is connected to every node and these connect as are either excitatory or inhibitory or irrelevant.


A single node is insufficient for many patricidal problems and large number of nodes is frequently used. The way nodes are connected determines how computations proceed and constitutes an important early design decision by a neural network developer. A brief discussion of biological neural networks is relevant, prior to examining artificial neural network arc ....etc

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We present a method to compute the delay-constrained multicast routing tree by employing chaotic neural networks. The experimental result shows that the noisy chaotic neural network (NCNN) provides an optimal solution more often compared to the transiently chaotic neural network (TCNN) and the Hopfield neural network (HNN). Furthermore, compared with the bounded shortest multicast algorithm (BSMA), the NCNN is able to find multicast trees with lower cost. ....etc

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Abstract
This study aims to determine the influence of the content of water and cement, water binder ratio, and
the replacement of fly ash and silica fume on the durability of high performance concrete (HPC) by using
artificial neural networks (ANNs). To achieve this, an ANNs model is developed to predict the durability of
high performance concrete which is expressed in terms of chloride ions permeability in accordance with
ASTM C1202-97 or AASHTO T277. The model is developed, trained and tested by using 86 data ....etc

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