# fast neural network

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### All the current Ann neuralnetwork algorithm Daquan

All the current Ann neural network algorithm DaquanOverview1 BP Neural network1.1 Main functions1.2 Advantages and Limitations2 RBF (radial basis function) neural network2.1 Main functions2.2 Advantages and Limitations3 Sensor Neural Network3.1 Main

### All the current Ann neuralnetwork algorithm Daquan

Http://blog.sina.com.cn/s/blog_98238f850102w7ik.htmlAll the current Ann neural network algorithm Daquan(2016-01-20 10:34:17)reproduced Tags: it Overview1 BP Neural network1.1 Main functions1.2 Advantages and

### Getting Started with neuralnetwork programming

Transfer from http://www.cnblogs.com/heaad/archive/2011/03/07/1976443.htmlThe main contents of this paper include: (1) Introduce the basic principle of neural network, (2) Aforge.net the method of realizing Feedforward neural Network, (3) Matlab to

### NeuralNetwork algorithm

Content Summary:(1) introduce the basic principle of neural network(2) Aforge.net method of realizing Feedforward neural network(3) the method of Matlab to realize feedforward neural network---cited Examples  In this paper, fisher's iris data set is

### Deep learning--the artificial neuralnetwork and the upsurge of research

Deep learning--the artificial neural network and the upsurge of researchHu XiaolinThe artificial neural network originates from the last century 40 's, to today already 70 years old. Like a person's life, has experienced the rise and fall, has had

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### From image to knowledge: an analysis of the principle of deep neuralnetwork for Image understanding

absrtact : This paper will analyze the basic principle of deep neural network to recognize graphic images in detail. For convolutional neural Networks, this paper will discuss in detail the principle and function of each layer in the network in the

### The basic principle of deep neuralnetwork to identify graphic images

absrtact : This paper will analyze the basic principle of deep neural network to recognize graphic images in detail. For convolutional neural Networks, this paper will discuss in detail the principle and function of each layer in the network in the

### Deep learning the significance of convolutional and pooled layers in convolutional neural networks

Why use convolution? In traditional neural networks, such as Multilayer perceptron (MLP), whose input is usually a feature vector, requires manual design features, and then the values of these features to form a feature vector, in the past decades

### Neuralnetwork summarizing __ Neuralnetwork

a summary of neural networks found that now every day to see things have a new understanding, but also to the knowledge of the past. Before listening to some of Zhang Yuhong's lessons, today I went to see some of his in-depth study series in the

### Application of CNN convolutional Neuralnetwork in natural language processing

Absrtact: As the core technology of most computer vision system, CNN has made great contribution in the field of image classification. Starting from the use case of computer vision, this paper introduces CNN and its advantages in natural language

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