Description: 神经网络与免疫算法的结合，用matlab编程实现一些小功能-Neural network with a combination of immune algorithm with matlab programming to achieve some small features Platform: |
Size: 79872 |
Author:杨玉琴 |
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Description: 人工神经网络(ANN)的泛化特性是神经网络最重要的特性,同时也是最不容易保证的特性。本程序对改进泛化的神经网络算法以及新兴的机器学习算法——支持向量机算法进行研究,-Artificial Neural Network (ANN) the generalization characteristics of neural networks are the most important characteristics, but also not easy to guarantee the most features. This procedure for improving the generalization of neural network algorithm, as well as the emerging machine learning algorithms- Support Vector Machine algorithm research, Platform: |
Size: 7168 |
Author:王旭 |
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Description: 利用BP神经网络对遥感图像进行地物的自动识别-The use of BP neural network of remote sensing images of the automatic recognition of features Platform: |
Size: 683008 |
Author:harvey |
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Description: 基于BP神经网络的遥感图像分类代码。从样本中提取崇明岛东滩十种地物的光谱特征，并训练BP网络，再利用网络进行分类-BP neural network-based remote sensing image classification code. Extracted from samples of 10 kinds of Chongming Island, Dongtan features of the spectral characteristics and to train BP network, and then use the network to classify Platform: |
Size: 1413120 |
Author:李琛 |
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Description: 利用bp神经网络对遥感图像进行分类，输入样本值后，根据样本值对遥感图像不同的地物进行分类，分类后计算每种地物所占面积-The use of bp neural network classification of remote sensing images, enter a sample value, based on the sample value of the different features of remote sensing image classification, classification features calculated for each share of area Platform: |
Size: 3072 |
Author:sun |
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Description: Based on the information processing functionalities of spiking neurons, a spiking neural network model is proposed to extract features from a visual image. The network is constructed with a conductance-based integrate-and-fire neuron model and a set of specific receptive fields. The properties of the network are detailed in this paper. Simulation results show that the network is able to perform image feature extraction within a time interval of 100 ms. This processing time is consistent with the human visual system. The demonstrations show how the network can extract right-angle contours in a visual image. Based on this principle, many other image features can be extracted by analogy. The parallel processing mechanism of this network model is very promising for a hardware implementation based on VLSI or FPGA technology. Platform: |
Size: 288768 |
Author:sacoura31 |
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Description: a transmission line fault location model which is based on an Elman recurrent network
(ERN) has been presented for balanced and unbalanced short circuit faults. All fault situations with
different inception times are implemented on a 380-kV prototype power system. Wavelet transform
(WT) is used for selecting distinctive features about the faulty signals. The system has the advantages of
utilizing single-end measurements, using both voltage and current signals. ERN is able to determine the
fault location occurred on transmission line rapidly and correctly as an important alternative to standard
feedforward back propagation networks (FFNs) and radial basis functions (RBFs) neural networks. Platform: |
Size: 761856 |
Author:charlie |
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Description: High information redundancy and correlation in face images result in efficiencies when such images are used directly for recognition. In this paper, discrete cosine transforms are used to reduce image information redundancy because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. We demonstrate experimentally that when DCT coefficients are fed into a backpropagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. This makes DCT-based face recognition much faster than other approaches.-High information redundancy and correlation in face images result in inefficiencies when such images are used directly for recognition. In this paper, discrete cosine transforms are used to reduce image information redundancy because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. We demonstrate experimentally that when DCT coefficients are fed into a backpropagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. This makes DCT-based face recognition much faster than other approaches. Platform: |
Size: 25600 |
Author:mhm |
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Description: 人工神经网络就是模拟人思维的第二种方式。这是一个非线性动力学系统，其特色在于信息的分布式存储和并行协同处理。虽然单个神经元的结构极其简单，功能有限，但大量神经元构成的网络系统所能实现的行为却是极其丰富多彩的。
-Simulation of artificial neural network is a second way of human thinking. This is a nonlinear dynamic system, which features a distributed information storage and parallel co-processing. Although the structure of single neurons is extremely simple, limited functionality, but a large number of neurons in a network system can realize the behavior is very colorful. Platform: |
Size: 5120 |
Author:prince |
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Description: The purpose of this work is to identify a given face image using main features of face. The dimensionality of face image is reduced by the Principal component analysis (PCA, using eigenfaces method) and the recognition is done by the Back propagation Neural Network (BPNN). Platform: |
Size: 3113984 |
Author:amine |
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Description: hopfield神经网络的matlab仿真真程序源码，能实现非常好的功能。 可直接使用。
-matlab simulation of the Hopfield neural network, real program source code, can achieve very good features. Can be used directly. Platform: |
Size: 1024 |
Author:noahkk |
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Description: Major features
BNT supports many types of conditional probability distributions (nodes), and it is easy to add more.
Tabular (multinomial)
Gaussian
Softmax (logistic/ sigmoid)
Multi-layer perceptron (neural network)
Noisy-or
Deterministic
Platform: |
Size: 12275013 |
Author:SunStacy |
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Description: In this paper, an attractive approach for teaching genetic algorithm has been
presented. This approach is based primarily on using MATLAB in
implementing the genetic operators: crossover, mutation, and selection. An
advantage of using such an approach is that the student becomes familiar with
some advanced features of MATLAB, and furthermore, with the availability of
other MATLAB Toolboxes such as The Control Systems Toolbox, Neural
Network Toolbox and Fuzzy Logic Toolbox, it is possible for the student to
develop genetic algorithm-based approaches to designing intelligent systems,
which could lead to his/ her final year or MSc project. Platform: |
Size: 98304 |
Author:jacob1717 |
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Description: This project provides matlab class for implementation of convolutional neural networks. This networks was developed by Yann LeCun and have sucessfully used in many practical applications, such as handwritten digits recognition, face detection, robot navigation and others (see references for more info). Because of some architectural features of convolutional networks, such as weight sharing it is imposible to implement it using Matlab Neural Network Toolbox without it s source modifications. Platform: |
Size: 627712 |
Author:郭志 |
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Description: In this report, we devise a methodology for identifying the species of an iris amongst 3 based on 4 distinctive features. We first cover the constitution of the data set and input patterns. We then determine the layout and structure of the neural network we will use for the classification. We continue by testing the network in real life conditions. We conclude with a review of the methods used, and how they could be improved. Platform: |
Size: 955392 |
Author:ryma |
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Description: 一个简易的神经网络模型，
一个对象具有4种特征，现设有3个对象，学习完成后，输入4个特征数据，能够得到属于哪一个对象类型(A simple neural network model,
An object has 4 features, and now has 3 objects, after learning, input 4 characteristic data, which type of object can be obtained) Platform: |
Size: 2048 |
Author:快乐阿通
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Search - features neural network matlab