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adapterSystemPaper
- 论文标题:自适应模糊系统在手写体数字识别中的应用研究 作者:张镭 作者专业:计算机软件人工智能 导师姓名:黄战 授予学位:硕士 授予单位:暨南大学 授予学位时间:19990501 论文页数:59页 文摘语种:中文文摘 分类号:TP18 TP391.4 关键词:手写体数字 自适应 模糊逻辑 神经网络 模式识别 摘要:该文针对模式识别的特点,构造了适合于模式识别问题的自适应模糊系统,对三种不同学习算法加以改进,在手写全数字识别上对分类器进行了实现,
1985528BP_RBF
- ADIAL Basis Function (RBF) networks were introduced into the neural network literature by Broomhead and Lowe [1], which are motivated by observation on the local response in biologic neurons. Due to their better approximation capabilities, si
caiqie
- 步态识别图像的初步裁切，对视频监控提取的图像进行裁切-The structures of the neural networks were designed using a constructive algorithm where the basic idea was to start with a small network,then add hidden units and weights incrementally until a satisfactory solution be foun
shibie
- 基于bp神经网络的车牌字符识别源程序，采用字符比对的方式进行切割-The structures of the neural networks were designed using a constructive algorithm where the basic idea was to start with a small network,then add hidden units and weights incrementally until a satisfactory solution b
SourceCode
- neural-network模型中，在產生一個輸出值前units轉換它們的net-input數值為一個activation value並視為一個中介的步驟。很多架構省略這個中介的步驟並且直接到輸出值的產生。在這裡，先忽略這個activation value的複雜度，我們首要的工作是output value輸出值的產生。我們以一個微分方程式的形式來表示一個unit的output value。就好像是生物學中所提的同等事物一樣，units的輸出值是時間的動態函數。-neural-network mo
nc_tanker
- Radial Basis Function Neural Controller for Tanker Ship Heading Regulation (using only 9 receptive field units)
ANN
- 这是一个matlab程序用于构建人工神经网络模型，可以随意设置层数和单元个数！-This is a matlab program for building artificial neural network model can arbitrarily set the number of layers and units!
AHU
- 神经网络建立的空调系统空气处理单元模型；simulink模型mdl，附带相关数据及归一化处理程序-Air-conditioning system neural network model of air handling units simulink model mdl, with relevant data and normalization process
GPU-CUDA001
- 文章介绍如何使用CUDA实现神经网络，并把他应用在GPU图像处理单元上。 -An Artificial Neural Network is an information processing method that was inspired by the way biological nervous systems function, such as the brain, to process information. It is composed of a large number of
using-adaptive-chebyshev
- 提出了一种基于自适应 Chebyshev 多项式神经网络(ACNN)的 Logistic 混沌系统控制算法。该算法采用 Chebyshev 正交多项式作为神经网络的激励函数, 构建 Logistic 混沌系统的预测与控制模型。为了保证算法的稳定性, 提出和证明了收敛定 理, 并利用自适应学习率算法提高神经网络的学习效率和收敛速度。通过采用自适应 Chebyshev 神经网络直接学习 Logistic 混 沌系统的动态特性, 并对系统实施目标函数控制。实验仿真结果表明, 该算法在 L
ABCNNTrain
- Training Artificial Neural Network. XOR Problem. Summation Units, Log-Sigmoid Neurons with Biases. Input Layer: 2, Hidden Layer: 2, Output Layer: 1 neurons. Returns mean square error between desired and actual outputs. Reference Pape
Fault-Detection-and-Isolation-in-Robotic-Manipula
- In this work, Artificial Neural Networks are employed in a Fault Detection and Isolation scheme for robotic manipulators. Two networks are utilized: a Multilayer Perceptron is employed to reproduce the manipulator dynamical behavior, generating a res
Introduction
- An Artificial Neural Network is a network of many very simple processors ("units"), each possibly having a (small amount of) local memory. The units are connected by unidirectional communication channels ("connections"), which carry numeric (as oppos
road
- BP神经网络预测公路运量 1.问题的描述 公路运量主要包括公路的客运量和公路货运量两个方面。据研究，某地区的公路运量主要与该地区的人数、机动车数量和公路面积有关，表1给出了20年得公路运量相关数据，表中人数和公路客运量的单位为万人，机动车数量单位为万两，公路面积的单位为万平方千米，公路货运量单位为万吨。 根据有关部门数据，该地区2010年和2011年的人数分别为73.39和75.55万人，机动车数量分别为3.9635和4.0975万辆，公路面积将分别为0.9880和1.0268万平
annlyap
- 最小RMSE神经网络方法计算Lyapunov指数的matlab函数。-This M-file calculates Lyapunov exponents with minimum RMSE neural network. After estimation of network weights and finding network with minimum BIC, derivatives are calculated. Sum of logarithm of QR decomposition
bp-neural-network-02
- BP神经网络隐单元个数不同造成误差精度以及训练时间不同-BP neural network the number of hidden units caused the error accuracy and training time
cllib
- CLLIB is a varied collection of Common lisp tools and routines in CLOCC. -CLLIB is a varied collection of Common lisp tools and routines in CLOCC. Includes: ■ "guess the animal" game simple neural net (AI) ■ autoload function and snarfi
61046606ABCNNTrain
- Training Artificial Neural Network. XOR Problem. Summation Units, Log-Sigmoid Neurons with Biases. Input Layer: 2, Hidden Layer: 2, Output Layer: 1 neurons. Returns mean square error between desired and actual outputs. Reference Papers: D. Karaboga,
ABCNNTrain
- Training Artificial Neural Network. XOR Problem. Summation Units, Log-Sigmoid Neurons with Biases. Input Layer: 2, Hidden Layer: 2, Output Layer: 1 neurons. Returns mean square error between desired and actual outputs. Reference Papers: D. Karaboga,
sample4
- 工神经网络（Artificial Neural Network）又称连接机模型，是在现代神经学、生物学、心理学等学科研究的基础上产生的，它反映了生物神经系统处理外界事物的基本过程，是在模拟人脑神经组织的基础上发展起来的计算系统，是由大量处理单元通过广泛互联而构成的网络体系，它具有生物神经系统的基本特征，在一定程度上反映了人脑功能的若干反映，是对生物系统的某种模拟，具有大规模并行、分布式处理、自组织、自学习等优点，被广泛应用于语音分析、图像识别、数字水印、计算机视觉等很多领域，取得了许多突出的成果