NeuroSolutions for MATLAB神经网络工具箱是MATLAB的技术推算职能的有效的附加工具，其允许用户在MATLAB中使用NeuroSolutions的职能。该工具箱将16种神经模型，5种进建算法和大量的利用在易用的用户界面中，险些对神经网络无相识的用户都能够使用该产品。该工具箱也与NeuroSolutions进行了，使得用户能够在NeuroSolutions中创建自界说的神经网络，并通过NeuroSolutions for MATLAB的用户界面在MATLAB中对其进行使用。

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神经网络工具箱是MATLAB，表接法式，使用方便，直观。它利用了业界的神经解决规划、神经网络和MATLAB中的人为智能。该软件能够让你集中精力解决你的问题，而花好多钱去寻找神经网络文件和自己开发算法。

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易于使用的

MATLAB的神经解能够被“险些不相识”神经网络的用户所利用。熟悉MATLAB的用户能够在几分钟内使用整个软件包。您能够将NeuroSolutions用于MATLAB的数据拟合、模式鉴别、功夫序列预测蹬爪用法式。

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的引擎

NeuroSolutions for MALTAB的特点是占有NeuroSolutions的神经网络引擎。23位和64位版本的MATLAB这是在MATLAB中使用神经网络的的步骤。对于较大的网络，使用NVIDIA CUDA?或OpenCL?与传统的CPU相比，使使培训功夫从幼时提高到分钟。

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神经解决规划的MATLAB套件：

NeuroSolutions for MATLAB也通过NeuroSolutions for MATLAB NeuroSolutions，该套件使用用户可能在NeuroSolutions中构建自界说网络，使用自界说解决规划向导为这些网络天生基于Windows的DLL，而后使用NeuroSolutions for MATLAB 中的DLL。

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工具箱有16个神经网络结构，7个进建算法和一大堆有效的实用工具，使人们可能利用神经网络的力量来解决复杂的现实问题。

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该工具箱以下神经网络的变形：

• 多层感知机

• 通用前馈神经网络

• 概率神经网络

• ？榛窬

• 向量机

• 部门循环神经网络

• 循环神经网络

• 延长循环神经网络

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除了Levenberg-Marquardt步骤以表，其还提供了以下6种进建算法

• 步骤法

• 动力法

• Quickprop法

• Delta-Bar-delta法

• 共轭梯度法

• Levenberg-Marquardt法

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工具箱还一些实用工具，符号数据转换，允许使用文本数据作为神经网络的输入。符号数据转换函数与反向转换函数一路使用，后者在实现工作后将数据转换回符号。图像扁平化工具将图像扁平化成一行数据，这样能够将其输入神经网络。机能指标函数揭示了神经网络与统计指标的训练成效。

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64位推算

提高机能与Windows 64位推算和的可执行代码显著缩短训练功夫！

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有弹性的反向传布（RProp）：

弹性反向传布是前馈人为神经网络中监督进建的一衷祠发式进建学法。与Levenberg-Marquardt相比，弹性反向传布是现有快的全职更新算法之一。

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R2013和64位MATLAB的神经规划已经被沉写，以更地使用MATLAB的新框架，对R2013/32位和64位装置。

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NeuroSolutions for MATLAB更新至V4，更新的内容如下：

● 提升了在Windows 64位系统上的推算机能，了可执行代码，培训功夫显著缩短。

● 弹性反向传布是前馈式人为神经网络中监督式进建的一张启发式的进建步骤，次于夸特法（Levenberg-Marquardt）。弹性反向传布是目前快的权值更新算法之一。

● 在使用夸特法网络中将NeuroSolutions加快器扩大组件与NVIDIA?和OpenCL?显卡或处置器一路使用，训练功夫从数幼时提高到短短几分钟—这是反向传布进建有力的一种大局。

● NeuroSolutions for MATLAB的大部门已经沉写使能以方式与MATLAB新的架构一路工作，R2013和32/64位的装置装置。

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信息

MATLAB版本：

2008、2009、2010、2011和2013（的版本为32和64位）

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【英文介绍】

NeuroSolutions for MATLAB neural network toolbox is a MATLAB
；add-in that is easy-to-use and intuitive. It leverages the industry leading power of NeuroSolutions neural networks and artificial intelligence inside MATLAB. The software allows you to concentrate on solving your problem without having to spend many hours persuing neural network literature and developing the algorithms yourself.

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Easy to Use

NeuroSolutions for MATLAB can be utilized by users with "next to no knowledge" of neural networks. Users who are familiar with MATLAB will be able to jump in and use the entire package within a few minutes. You can use NeuroSolutions for MATLAB for applications such as data fitting, pattern recognition, time-series prediction and much more.

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Powerful Engine

NeuroSolutions for MALTAB features the neural network engine from industry leading NeuroSolutions. Supporting both 32- and 64-bit versions of MATLAB it is the most powerful way to use neural networks in MATLAB. For larger networks, use NVIDIA CUDA™ or OpenCL™ to enable training time improvements from hours to minutes when compared to traditinal CPU's.

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NeuroSolutions for MATLAB Suite

NeuroSolutions for MATLAB is also integrated with NeuroSolutions through the NeuroSolutions for MATLAB Suite that enables users to build custom networks in NeuroSolutions, generate Windows-based DLL's for those networks using the Custom Solution Wizard and then use the DLL's inside NeuroSolutions for MATLAB.

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The toolbox features 16 neural network architectures, 7 learning algorithms and a host of useful utilities that enables one to employ the power of neural networks to solve complicated real-world problems.

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Neural Network Architectures:

Multilayer Perceptron

Generalized Feed Forward Network

Probabilistic Neural Network

Modular Neural Network

Support Vector Machine

Partially Recurrent Neural Network

Fully Recurrent Neural Network

?Time-Lag Recurrent Neural Network

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Learning Algorithms:

Step

Momentum

Resilent Backpropagation (RProp)

Quickprop

Delta-Bar-Delta

Conjugate Gradient

Levenberg-Marquardt

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The toolbox also includes several utilities including Symbolic Data Translation allows for using textual data as inputs to a neural network. The symbolic data translation function comes paired with the inverse translation function that translates data back to symbols once all other tasks are completed. The Image Flattening utility flattens an image into a single row of data, so that it can be fed into a neural network. The Performance Indicators function reveals how well the neural network has trained with statistical indicators.

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64-bit computing

Increase performance with Windows 64-bit computing and optimized executable code for significantly shorter training times!

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Resilient Backpropagation (RProp)

Resilient Backpropagation is a learning heuristic for supervised learning in feed forward artifical neural networks. Next to Levenberg-Marquardt, Resilient Backpropagation is one of the fastest weight updating algorithms available.

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NeuroSolutions Accelerator Add-on

See training time improvements from hours to minutes using NVIDIA™ and OpenCL™ graphics cards or processors with the NeuroSolutions Accelerator add-on on networks using Levenberg-Marquardt - the most powerful form of back-propagation learning available.

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Supporting R2013 and 64-bit MATLAB

Much of NeuroSolutions for MATLAB has been rewritten to work with MATLAB's latest framework more optimally including support up to R2013 and 32- and 64-bit installations.

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Getting Started with NeuroSolutions for MATLAB

Visit our Video Library page for more videos on NeuroSolutions and related products.

Other Information

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Supported MATLAB Versions:

2008, 2009, 2010, 2011, 2012 & 2013 (32/64-bit for all supported versions)

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