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BP
- 反向传播算法也称BP算法,是一种神经网络学习的数学模型,解决多层前向神经网络的权系数优化-Back-propagation algorithm, also known as BP algorithm is a neural network study of the mathematical model and solve multi-layer feedforward neural network weights optimization
BP
- 我们最常用的神经网络就是BP网络,也叫多层前馈网络。BP是back propagation的所写,是反向传播的意思。-We are the most commonly used neural network is a BP network, also known as multi-layer feedforward network. BP is written by the back propagation is the meaning of back-propagation.
feedforward_with_GUI
- design and implementation of feedforward neural network with BP training algorithm.(include the GUI)
PID-control-based-BP
- 用一个多层前向神经网络,采用反向传播算法依据控制要求实时输出Kp、Ki、Kd,依次作为PID控制器的实时参数,代替传统PID参数靠经验的人工整定和工程整定,以达到对大迟延主气温系统的良好控制。-We use a multilayer feedforward neural network using back propagation algorithm and based on control requirements.This net can real-time output Kp, Ki, K
PID
- 前馈神经网络例程,BP神经网络,主要仿真了其功能原理-Feedforward neural network routines, BP neural network, the main principle of the simulation of its function
bp-matlab
- bp的matlab源代码 多层前馈网络用于图像压缩的网络模型、原理、算法及关键技术,并通过仿真实验说明了在BP神经网络图像压缩中,算法、激活函数和压缩率等参数的选择是至关重要的,它们与收敛时间以及重建图像的压缩性能息息相关。-the multilayer feedforward network for image compression network model, theory, algorithm and key technologies, by simulation illustrates
BP-neural-networks-algorithm
- 本程序为一个误差向后传播的三层前馈神经网络有指导的学习算法:Gauss变异动态调整BP算法中学习率参数和冲量系数-This program is a three-layer error back propagation feedforward neural networks supervised learning algorithm: the Gauss variation dynamically adjusts the learning rate in BP algorithm paramet
bp-solve
- BP网络是目前前馈式神经网络中应用最广泛的网络之一,实现BP算法训练神经网络完成XOR的分类问题。 设计要求: (1) 能够设置网络的输入节点数、隐节点数、网络层数、学习常数等各项参数; (2) 能够输入训练样本; (3) 实现BP算法的训练过程; (4) 实现训练过程的动态演示; (5) 训练完成后可输入测试数据进行测试。 -BP neural network is feedforward neural networks one of the most widel
BP-neural-network-prediction-method
- BP(Back Propagation)网络是1986年由Rumelhart和McCelland为首的科学家小组提出,是一种按误差逆传播算法训练的多层前馈网络,是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系,而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法,通过反向传播来不断调整网络的权值和阈值,使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层(input)、隐层(hide layer)和输出层(output layer)。-
bp-traffic-forecasts
- 使用前馈型神经网络(BP神经网络)进行交通预测的matlab源代码-Using feedforward neural networks (BP neural network) traffic forecasts matlab source code
GA-BP-algorithm
- Multilayer feedforward networks GA-BP hybrid learning algorithm
BP-ANN
- BP网络是一种按误差逆传播算法训练的多层前馈网络,目前应用较为广泛。它能学习和存贮大量的输入-输出模式映射关系,而无需事前揭示描述这种映射关系的数学方程。本文讲述了一种关于BP神经网络应用实例。-BP network is a back propagation algorithm by former Multilayer feedforward network, currently used more widely.They can learn and store a lot of input-
BP
- BP网络(Back Propagation),是1986年由Rumelhart和McCelland为首的科学家小组提出,是一种按误差逆传播算法训练的多层前馈网络,是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系,而无需事前揭示描述这种映射关系的数学方程。-Back Propagation (BP), a multi-layer feedforward neural network trained by the error back propagation al
BP网络
- BP(Back Propagation)网络是1986年由Rumelhart和McCelland为首的科学家小组提出,是一种按误差逆传播算法训练的多层前馈网络,是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入输出模式映射关系,而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法(梯度法),通过反向传播来不断调整网络的权值和阈值,使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层(input layer)、隐层(hide layer)和输出层(outpu
bp神经网络
- Matlab实现前向神经网络的方法 本文以Fisher的Iris数据集作为神经网络程序的测试数据集(Implementation of feedforward neural networks by Matlab)
BP
- BP(back propagation)神经网络是1986年由Rumelhart和McClelland为首的科学家提出的概念,是一种按照误差逆向传播算法训练的多层前馈神经网络,是目前应用最广泛的神经网络(BP Neural network is a concept proposed by scientists led by Rumelhart and McClelland in 1986. It is a multilayer feedforward neural network trained
BP神经网络程序
- 是一种按误差逆传播算法训练的多层前馈网络,是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系,而无需事前揭示描述这种映射关系的数学方程。(It is a multilayer feedforward network trained by error backpropagation algorithm, and is one of the most widely used neural network models. BP networks can learn a
BP神经网络的拓扑优化算法
- BP(back propagation)神经网络是1986年由Rumelhart和McClelland为首的科学家提出的概念,是一种按照误差逆向传播算法训练的多层前馈神经网络,是目前应用最广泛的神经网络(BP neural network is a concept put forward by scientists from Rumelhart and McClelland in 1986. It is a multilayer feedforward neural network traine
BP神经网络
- BP(back propagation)神经网络是1986年由Rumelhart和McClelland为首的科学家提出的概念,是一种按照误差逆向传播算法训练的多层前馈神经网络,是目前应用最广泛的神经网络。(BP (back propagation) neural network was founded in 1986 by Rumelhart and McClelland, led by the scientists put forward the concept of error backwa
BP
- BP网络(Back Propagation),是1986年由Rumelhart和McCelland为首的科学家小组提出,是一种按误差逆传播算法训练的多层前馈网络,是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系,而无需事前揭示描述这种映射关系的数学方程。(BP nntool is a multilayer feedforward network trained by error inverse propagation algorithm. It is one