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Description: This program demonstrates some function approximation capabilities of a Radial Basis Function Network.
The user supplies a set of training points which represent some \"sample\" points for some arbitrary curve. Next, the user specifies the number of equally spaced gaussian centers and the variance for the network. Using the training samples, the weights multiplying each of the gaussian basis functions arecalculated using the pseudo-inverse (yielding the minimum least-squares solution). The resulting network is then used to approximate the function between the given \"sample\" points. -This program demonstrates some function a pproximation capabilities of a Radial Basis Fu nction Network. The user supplies a set of train ing points which represent some "sample" point s for some arbitrary curve. Next, the user specifies the number of equally spaced Response centers and the variance for the netwo rk. Using the training samples, the weights multiplying each of the Gaussian ba sis functions arecalculated using the pseudo - inverse (yielding the minimum least-squares s middleware). The resulting network is then used to approximate the function between the given "sa mple "points.
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Size: 18685 |
Author: 陈伟 |
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Description: 用外积和法设计的权矩阵，不能保证p对模式全部正确的联想。若对记忆模式对加以限制（即要求p个记忆模式Xk是两两正交的），则用外积和法设计的BAM网具有较好的联想能力。 在难以保证要识别的样本（或记忆模式）是正交的情况下，如何求权矩阵，并保证具有较好的联想能力？这个问题在用BAM网络实现对字符的识别程序仿真中得到体现。我们做过尝试，用伪逆法求权矩阵，虽然能对未加干扰的字符全部进行识别，但对加有噪声的字符识别效果很差。至于采用改变结构和其他算法的方法来求权矩阵，将是下一步要做的工作。-foreign plot and the design of the power matrix, p is no guarantee that all the correct pattern association. If memory model, the limit (that is, p-memory model Xk is orthogonal to the February 2), then foreign plot and design of the BAM network has good ability to think. It is difficult to ensure the samples to identify (or memory mode) is orthogonal circumstances, the right to seek ways matrix, and to ensure that the association has good ability? The problem with the BAM network of characters identification procedures simulation can be manifested. We did try to use pseudo - inverse matrix for the right, although they would not increase the interference of the characters in the identification of all, However, a pair of noise increases the effects of poor character recognition. As for the
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Size: 231686 |
Author: 东方云 |
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Description: This program demonstrates some function approximation capabilities of a Radial Basis Function Network.
The user supplies a set of training points which represent some "sample" points for some arbitrary curve. Next, the user specifies the number of equally spaced gaussian centers and the variance for the network. Using the training samples, the weights multiplying each of the gaussian basis functions arecalculated using the pseudo-inverse (yielding the minimum least-squares solution). The resulting network is then used to approximate the function between the given "sample" points. -This program demonstrates some function a pproximation capabilities of a Radial Basis Fu nction Network. The user supplies a set of train ing points which represent some "sample" point s for some arbitrary curve. Next, the user specifies the number of equally spaced Response centers and the variance for the netwo rk. Using the training samples, the weights multiplying each of the Gaussian ba sis functions arecalculated using the pseudo- inverse (yielding the minimum least-squares s middleware). The resulting network is then used to approximate the function between the given "sa mple "points.
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Size: 18432 |
Author: 陈伟 |
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Description: 用外积和法设计的权矩阵，不能保证p对模式全部正确的联想。若对记忆模式对加以限制（即要求p个记忆模式Xk是两两正交的），则用外积和法设计的BAM网具有较好的联想能力。 在难以保证要识别的样本（或记忆模式）是正交的情况下，如何求权矩阵，并保证具有较好的联想能力？这个问题在用BAM网络实现对字符的识别程序仿真中得到体现。我们做过尝试，用伪逆法求权矩阵，虽然能对未加干扰的字符全部进行识别，但对加有噪声的字符识别效果很差。至于采用改变结构和其他算法的方法来求权矩阵，将是下一步要做的工作。-foreign plot and the design of the power matrix, p is no guarantee that all the correct pattern association. If memory model, the limit (that is, p-memory model Xk is orthogonal to the February 2), then foreign plot and design of the BAM network has good ability to think. It is difficult to ensure the samples to identify (or memory mode) is orthogonal circumstances, the right to seek ways matrix, and to ensure that the association has good ability? The problem with the BAM network of characters identification procedures simulation can be manifested. We did try to use pseudo- inverse matrix for the right, although they would not increase the interference of the characters in the identification of all, However, a pair of noise increases the effects of poor character recognition. As for the
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Size: 231424 |
Author: 东方云 |
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Description: 数字图像获取, 处理及实践应用源代码——很多有用的图像处理的源代码：图像显示（原图、抖动），图像增强（灰度变换、直方图均衡、多种滤波器、伪彩色增强等），图像复原（运动模糊、逆滤波等等），图像变换（傅立叶变换、快速傅立叶变换、离散余弦变换、沃尔什变换、霍特林变换、小波变换、小波反变换），图像编码（霍夫曼编码、香浓-费诺编码、算术编码、位平面编码等），图像识别。-Digital image acquisition, processing and practical application source code- a lot of useful image processing source code: Image Display (image, jitter), image enhancement (gray-scale transformation, histogram equalization, multi-filter, pseudo-color enhancement, etc. ), image restoration (motion blur, inverse filtering, etc.), image transform (Fourier transform, fast Fourier transform, discrete cosine transform, Walsh transform, Hotelling transform, wavelet transform, wavelet transform), image coding (Huffman coding, Shannon- Fenno coding, arithmetic coding, bit plane coding, etc.), image recognition.
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Size: 5184512 |
Author: 郑忠恒 |
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Description: 一个梯度优化算法的实例(演示)。。。。线性判别分析的伪逆算法程序（matlab6.5）-A gradient optimization algorithm examples (demo). . . . Linear Discriminant Analysis of the pseudo-inverse algorithm procedure (matlab6.5)
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Size: 3072 |
Author: 吴雪文 |
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Description: 给出了如何使用伪逆滤波器的matlab代码-give a matlab code of pseudo-inverse filter
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Size: 1024 |
Author: 栾 |
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Description: 使用VisualC++实现的伪逆矩阵的计算方法，Dlg编程。-Using VisualC++ implementation of the pseudo-inverse matrix method of calculation, Dlg programming.
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Size: 2122752 |
Author: 贾易 |
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Description: pseudo inverse kinematics
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Size: 10240 |
Author: manju |
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Description: file contains of moore_penrose pseudo inverse including example and solution
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Size: 58368 |
Author: ann |
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Description: 快速脊波逆变换。也称为伴随和伪逆。也成为快速三角波逆变换。-Fast Inverse Curvelet Transform.This is in fact the adjoint, also the pseudo-inverse
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Size: 3072 |
Author: 胡大帅 |
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Description: 基于CLAPACK的矩阵求伪逆的运算函数，效率非常好，需要自己编译下CLAPACK库才可以使用-LAPACK matrix pseudo-inverse operator function, the efficiency is very good, need to compare his own Lower CLAPACK library can only be used
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Size: 1024 |
Author: 王宏 |
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Description: 给出了如何使用伪逆滤滤波器的matlab代码
-How to use the pseudo-inverse filter filter matlab code
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Size: 1024 |
Author: xiajiang |
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Description: weiner and pseudo inverse filter
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Size: 297984 |
Author: Mrinal |
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Description: 矩阵求伪逆，在图像，机器人，压缩文件方面都有很大的用处-Matrix pseudo-inverse, compressed files have great usefulness in the image, the robot
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Size: 4096 |
Author: 沙佑平 |
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Description: RBF 神经网络 Pseudo Inverse -RBF neural network Pseudo Inverse
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Size: 83968 |
Author: wyl |
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Description: 很好的广义逆平差程序,包括伪逆、正则逆等，值得推荐-Good generalized inverse of the adjustment program, including pseudo-inverse is the inverse, it is recommended
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Size: 1024 |
Author: shubao |
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Description: 利用多用方法进行数字图像去模糊实例，便于初学者理解反卷积去模糊、伪逆去模糊等基本算法-Example scripts for image debluring, try to give general introduction of some basic algorithms, such as pseudo inverse debluring.
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Size: 1024 |
Author: zhouxiong |
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Description: //奇异值分解法求双精度浮点数矩阵的广义逆
//功能：利用奇异值分解求解一般的m×n阶实矩阵A的广义逆A+。
//方法说明：设m×n阶实矩阵A的奇异值分解式为
//其中 Σ = diag(σ0, σ1, ……,σp)(p≤min(m,n) -1 )且σ0≥σ1≥……≥σp＞0
//设U = （U1,U2）,其中U1为U中前P+1列列正交向量组构成的m×(p+1)矩阵；V = (V1，V2)，其中V1为前P+1列//列正交向量组构成的n×(p+1)矩阵。则A的广义逆为：
//A+ = V1ΣU1T
//以求3×4矩阵的逆矩阵为例。-pseudo-inverse matrix
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Size: 4096 |
Author: 杜晓莉 |
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Description: 伪逆分类法的matlab实现，包含训练和测试部分-Pseudo-inverse classification matlab realization, including training and testing parts
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Size: 1024 |
Author: sunny |
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