ABSTRACT :
Heterogeneous types of gene expressions may provide a better insight into the biological role of gene interaction with the environment, disease development and drug effect at the molecular level. In this paper for both exploring and prediction
purposes a Time Lagged Recurrent Neural Network with trajectory learning is proposed for identifying and classifying the gene functional patterns from the heterogeneous nonlinear time series microarray experiments. The pr ....etc

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Unsupervised Neural Networks
ABSTRACT
Self organizing maps are generally used in many fields like bio-informatics, neural networks¦.It is basically used for the grouping of data. In decision making we reach a conclusion by making certain tests to the input given to the system. We will study the outputs obtained by the tests and reach a solution. Consider a decision making system which checks whether a cloth is wet or not. If we give the parameters of cloth we need to know whether it ....etc

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Holographic associative memory can be considered as a type of artificial neural network, which is having close association with the family of analog, correlation-based, stimulus-responsive memories. In Holographic associative memory, the information is mapped on to the phase orientation of complex numbers operating. The ability of holographs in carrying out effective associative memory tasks, generalization and pattern recognition with changeable attention has given holographic memory the cutting edge over others. Natural memory has the capacit ....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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Definition

These notes provide an introduction to unsupervised neural networks, in particular Kohonen self-organizing maps; together with some fundamental background material on statistical pattern recognition.

One question which seems to puzzle many of those who encounter unsupervised learning for the first time is how can anything useful be achieved when input information is simply poured into a black box with no provision of any rules as to how this information should be stored, or examples of the various groups into which this informa ....etc

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Definition

These notes provide an introduction to unsupervised neural networks, in particular Kohonen self-organizing maps; together with some fundamental background material on statistical pattern recognition.

One question which seems to puzzle many of those who encounter unsupervised learning for the first time is how can anything useful be achieved when input information is simply poured into a black box with no provision of any rules as to how this information should be stored, or examples of the various groups into which this informa ....etc

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A NEURAL NETWORK MODEL FOR DETECTING ANAMALOUS TRAFFIC IMPLEMENTING SELF-ORGANIZING MAPS
Presented By:
G Vijay Kumar 1 Sumalatha 2 A Ajay Kumar 3 K V Ramana

department of ECE, VR Siddhartha Engg. College, Vijayawada, India
Department of CSE, JNTU College of Engg., JNTU, Kakinada, India
Department of CSE, JNTU College of Engg., JNTU, Kakinada, India 4Department of CSE, Sri Prakash Engineering College, TUNI, Andhra Pradesh, India

ABSTRACT
Integrated Network-Based Ohio University Network ....etc

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Holographic associative memory can be considered as a type of artifical neural network, which is having close association with the family of analog, correlation-based, stimulus-responsive memories. In Holographic associative memory, the information is mapped on to the phase orientation of complex numbers operating. The ability of holographs in carrying out effective associative memory tasks, generalization and pattern recognition with changeable attention has given holographic memory the cutting edge over others. Natural memory has the capacity ....etc

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send me the matlab code for self organizing tree algorithm for image classification ....etc

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Self-Interested Routing in Online Environments

Abstract

A recent trend in routing research is to avoid inefficiencies in network-level routing by allowing hosts to either choose routes themselves (e.g., source routing) or use overlay routing networks (e.g., Detour or RON). Such approaches result in Self-interested routing, because routing decisions are no longer based on system-wide criteria but are instead designed to optimize host-based or overlay-based metrics. A series of theoretical results showing that Self-inte ....etc

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