Description: 该算法实现了基本的人工神经网络SOM模型，适合初学者可在其基础上进行相应的拓展-The algorithm realizes the basic artificial neural network SOM model, which is suitable for beginners to expand on the basis of the corresponding Platform: |
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Author:保见 |
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Description:
深度学习的概念源于人工神经网络的研究。含多隐层的多层感知器就是一种深度学习结构。深度学习通过组合低层特征形成更加抽象的高层表示属性类别或特征，以发现数据的分布式特征表示。[1]
深度学习的概念由Hinton等人于2006年提出。基于深信度网(DBN)提出非监督贪心逐层训练算法，为解决深层结构相关的优化难题带来希望，随后提出多层自动编码器深层结构。此外Lecun等人提出的卷积神经网络是第一个真正多层结构学习算法，它利用空间相对关系减少参数数目以提高训练性能。[1]
深度学习是机器学习研究中的一个新的领域，其动机在于建立、模拟人脑进行分析学习的神经网络，它模仿人脑的机制来解释数据，例如图像，声音和文本。
同机器学习方法一样，深度机器学习方法也有监督学习与无监督学习之分．不同的学习框架下建立的学习模型很是不同．例如，卷积神经网络（Convolutional neural networks，简称CNNs）就是一种深度的监督学习下的机器学习模型，而深度置信网（Deep Belief Nets，简称DBNs）就是一种无监督学习下的机器学习模型。
-Research on the concept of deep learning the artificial neural network. Multi hidden layer of multi-layer perceptron is a deep learning structure. Deep learning features a more abstract representation of a higher level representation of a feature class or feature to find data. [1]
Deep learning s concept by Hinton et al. In 2006. Based on the (DBN), a non supervised greedy layer by layer training algorithm is proposed to solve the problems of the deep structure. In addition, the convolutional neural network proposed by Lecun et al is the first real multi layer structure learning algorithm, which uses the relative relationship between the number of parameters to improve the training performance. [1]
Deep learning is a new field in machine learning research. The motivation is to establish and simulate the human brain to analyze the learning of neural network, which simulates the human brain mechanism to explain the data, such as image, sound and text.
Convolutional (neural) net Platform: |
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Author:Francis |
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Description: 基于简单bp人工神经网络的的简单分类识别的程序，主要是对裂纹类型的识别-Based on a simple artificial neural network bp simple classification procedure is to identify the main types of crack Platform: |
Size: 1024 |
Author:wangxiaomin |
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Description: 用matlab实现的进行水位预报的人工神经网络的基于样本数据进行整理采集和训练得到模型的源代码，以用于预报-the complementation of artificial neural network of training samples using matlab Platform: |
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Author:轩紫 |
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Description: the combination of artificial neural network (ANN) and ant colony optimization (ACO) algorithm has been utilized for modeling and reducing NOx and soot emissions a direct injection diesel engine. A feed-forward multi-layer perceptron (MLP) network is used to represent the relationship between the input parameters (i.e., engine speed, intake air temperature, rate of fuel mass injected, and power) on the one hand and the output parameters-the combination of artificial neural network (ANN) and ant colony optimization (ACO) algorithm has been utilized for modeling and reducing NOx and soot emissions a direct injection diesel engine. A feed-forward multi-layer perceptron (MLP) network is used to represent the relationship between the input parameters (i.e., engine speed, intake air temperature, rate of fuel mass injected, and power) on the one hand and the output parameters Platform: |
Size: 3072 |
Author:golalipour |
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Description: Face is a primary focus of attention in social intercourse, playing a major role in conveying identity and
emotion. The human ability to recognize faces is remarkable. People can recognize thousands of faces learned throughout
their lifetime and identify familiar faces at a glance even after years of separation. This skill is quite robust, despite large
changes in the visual stimulus due to viewing conditions, expression, aging, and distractions such as glasses, beards or
changes in hair style. In this work, a system is designed to recognize human faces depending on their facial features. Also
to reveal the outline of the face, eyes and nose, edge detection technique has been used. Facial features are extracted in the
form of distance between important feature points. After normalization, these feature vectors are learned by artificial
neural network and used to recognize facial image. Platform: |
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Author:fatemeh |
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Description: As signatures are widely accepted bio-metric for authentication and identification of a person because every person
has a distinct signature with its specific behavioral property, so it is very much necessary to prove the authenticity of signature
itself. There are various techniques to signature recognition with a lot of scope of research. In this paper off-line signature
recognition and verification system using Artificial Neural Network (ANN) is purposed. The purposed network based upon the
adaption of ANN to recognized signature to connected type pattern. The purpose ANN was trained with back propagation with
momentum and adaptive learning rate. A triple hidden layer ANN with 100 inputs 58.38.20 hidden neurons layers and 5 neurons
in output layers gives best results as compared with other networks. This paper represents a brief review on various approaches
used in signature verification systems. Platform: |
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Author:shiwi |
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Description: 基于人工神经网络的常用数字信号调制，bVyAoKQ参数DC-DC部分采用定功率单环控制，结合PCA的尺度不变特征变换(SIFT)算法，包含优化类的几个简单示例程序，pVELPuz条件是一种双隐层反向传播神经网络，验证可用。- The commonly used digital signal modulation based on artificial neural network, bVyAoKQ parameter DC-DC power single-part set-loop control, Combined with PCA scale invariant feature transform (SIFT) algorithm, Optimization class contains several simple sample programs, pVELPuz condition Is a two hidden layer back propagation neural network, Verification is available. Platform: |
Size: 6144 |
Author:sbqtvq |
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Description: 部分实现了追踪测速迭代松弛算法，AIfRlGh参数基于人工神经网络的常用数字信号调制，在matlab R2009b调试通过，是机器学习的例程，UwzAqtQ条件是学习PCA特征提取的很好的学习资料，基于互功率谱的时延估计。- Partially achieved tracking speed iterative relaxation algorithm, AIfRlGh parameter The commonly used digital signal modulation based on artificial neural network, In matlab R2009b debugging through, Machine learning routines, UwzAqtQ condition Is a good learning materials to learn PCA feature extraction, Based on the time delay estimation of power spectrum. Platform: |
Size: 6144 |
Author:tuzaqa |
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