Feed-Forward and Feedback Neural Networks
Topographic mappings and feed-forward neural networks
... This is a highly relevant observation, as one existing approach to producing a transformational topo- graphic mapping is to generate a configuration using Sammon’s standard procedure, and then fit a parameterised model ...
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Classification of Arecanut using Neural Networks with Feed forward Techniques
... Keywords - GLCM, Shape Features, Feed-forward NN. 1. INTRODUCTION Arecanut palm is one of the significant commercial crops of India. Arecanut is the main plantation crop of costal and southern districts of ...
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An Evolutionary Approach to Training Feed-Forward and Recurrent Neural Networks.
... The gene structure used by Krishnan is an attempt to overcome the problems associated with encoding real numbers onto a chromosome represented as a bit string. In the 2DELTA-GANN method, each gene on the chromosome is a ...
Fingerprint Liveness Detection based on Feed Forward Neural Networks
... creature neural framework, a neuron is seen to get input signals from its dendrites and delivering yield motions along its ...the neural framework computational model, the signs that come the axons work ...
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Foreground-Background Separation by Feed-forward Neural Networks in Old Manuscripts
... regression neural network, for high precision OCR algorithms over a limited number of document ...regression neural network to obtain the optimal threshold ...
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Cell Nuclei Segmentation And Classification Using Feed Forward Neural Networks
... to feed forward neural network for classification ...The Feed Forward neural network consists of neurons,that are arranged into the ...This networks information flows only ...
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Challenges to Multi-Layer Feed Forward Neural Networks in Intrusion Detection
... multi-layer feed forward neural network intrusion detection system is an important problem according to Bhaskar, Kamath and Moitra ...multi-layer feed forward neural network is ...
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Generalization properties of feed-forward neural networks trained on Lorenz systems
... Abstract. Neural networks are able to approximate chaotic dynamical systems when provided with training data that cover all relevant regions of the system’s phase ...of feed-forward ...
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Partial Learning Machine: A New Learning Scheme for Feed Forward Neural Networks
... Keywords: Neural networks, Partial learning machine (PLM), Extreme learning machine (ELM), Back-propagation algorithm ...traditional Feed Forward Neural Network (FNN) learning methods ...
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Optimal Model for Path Loss Predictions using Feed-Forward Neural Networks
... single-layered feed-forward neural network architecture, comprised of six input neurons and one output neuron, was designed for model training and development, as shown in Figure ...
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A comparative assessment of Feed-Forward and Convolutional Neural Networks for the classification of prostate lesions
... S vs. N vs. H 0.628 0.648 0.824 0.892 The first thing to notice from the results is that always the over-sampling strategy outperformed the under-sampling, regardless of the neural network architecture used. This ...
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A Novel Strategy for Weight Initialization in Sigmoidal Feed-forward Artificial Neural Networks
... Abstract—Among the various parameters of a neural network, the initial values of the weights and biases pertaining to each artificial neuron have been given a lot of importance. In this paper, a novel method of ...
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Feed-Forward Neural Networks Need Inductive Bias to Learn Equality Relations
... Since neural networks are currently by far the most popular machine learning method, it seems of interest whether they can learn ...that feed-forward networks are universal ...
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Cooperative coevolution of feed forward neural networks for financial time series problem
... of Feed Forward Neural Networks for Financial Time Series Problem Shelvin Chand and Rohitash Chandra Abstract— Intelligent financial prediction systems guide in- vestors in making good ...
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FEEDBACK AND FEED-FORWARD FOR PROMOTING PROBLEM-BASED LEARNING
... Blackboard played a critical part in the success of students in this course, but also posed some concerns. PBL in an online environment requires careful attention to the learning and teaching tools in this virtual ...
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Comparison of Feed-forward and Feedback LFSR for High Reliability
... Abstract Error correction is one of the important technique for detecting and correcting errors in communication channels, memories etc., Errors are associated with all types of memories. But the NAND FLASH memories are ...
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ParkinsoNET: Estimation of UPDRS Score using Hubness-aware Feed-Forward Neural Networks
... The data recorded during spontaneous usage of smartphones and tablets was originally not designed for diagnostic purposes, therefore, even the most useful pieces of the data can only be expected to be weakly correlated ...
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Part of Speech Driven Cross Lingual Pronoun Prediction with Feed Forward Neural Networks
... For some language pairs, pronoun trans- lation is a discourse-driven task which re- quires information that lies beyond its lo- cal context. This motivates the task of predicting the correct pronoun given a source ...
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Feed forward neural networks and genetic algorithms for automated financial time series modelling
... Formal and applied methods are investigated for combining feed-forward Neural Networks and Genetic Algorithms (GAs) into a single adaptive/learning system for automated time series forec[r] ...
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Leukemia Diagnosis using Back Propagation Multi-layer Feed Forward Neural Networks
... ABSTRACT: The term “Leukemia” refers to cancer of the blood cells. The presence of Eosinophil, Neutrophil, Lymphocyte, Basophil, and Monocyte in the blood test and the bone marrow indicates that the cells are influenced ...
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