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Description: The Molgedey and Schuster decorrelation algorithm, having square mixing matrix and no noise . Truncation is used for the time shifted matrix, and it is forced to be symmetric . The delay Tau is estimated .
The number of independent components are calculated using Bayes Information Criterion (BIC), with PCA for dimension reduction.-The Molgedey and Schuster decorrelation algorithm, having square mixing matrix and no noise . Truncation is used for the time shifted matrix, and it is forced to be symmetric . The delay Tau is estimated . The number of independent components are calculated using Bayes Information Criterion (BIC), with PCA for dimension reduction.
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Author: 海心 |
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Description: This directory contains the following:
[fajd.m] The FAJD algorithm for finding the approximate general
(non-orthogonal) joint diagonalizer of a set of matrices.
[test.m] A routine to demonstrates the way to call FAJD after
generating a set of target-matrices.
[average_performance.m] A routine that compares the average
performance of FAJD with different fixed processing parameters.
[sir.m] A function that calculates the signal to interference ratio
(SIR) of a combined demixing-mixing matrix.
Contributed by Xi-Lin Li (e-mail: li-xl04@mails.tsinghua.edu.cn).
Comments, bug reports, questions and suggestions are welcome.
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Author: 薛耀斌 |
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Description: This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the marginal likelihood [1]. The sufficient statistics are estimated by either variational mean field theory with the linear response correction or by adaptive TAP mean field theory [2,3]. The mean field equations are solved by a belief propagation method [4] or sequential iteration. The computational complexity is N M^3, where N is the number of time samples and M the number of sources.
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Author: 陈互 |
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Description: This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the marginal likelihood [1]. The sufficient statistics are estimated by either variational mean field theory with the linear response correction or by adaptive TAP mean field theory [2,3]. The mean field equations are solved by a belief propagation method [4] or sequential iteration. The computational complexity is N M^3, where N is the number of time samples and M the number of sources.
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Author: 陈互 |
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Description: The Molgedey and Schuster decorrelation algorithm, having square mixing matrix and no noise . Truncation is used for the time shifted matrix, and it is forced to be symmetric . The delay Tau is estimated .
The number of independent components are calculated using Bayes Information Criterion (BIC), with PCA for dimension reduction.-The Molgedey and Schuster decorrelation algorithm, having square mixing matrix and no noise . Truncation is used for the time shifted matrix, and it is forced to be symmetric . The delay Tau is estimated . The number of independent components are calculated using Bayes Information Criterion (BIC), with PCA for dimension reduction.
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Author: 海心 |
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Description: 该文用不同的本构关系研究了金属衬底手征
涂层的吸波特性,并进行了比较. 结果表明,只要手征媒质的宏观电磁参数统一后,就能使用不同的本构关系得到
相同的结果,进而揭示本构关系的等效性. 数值计算结果表明,在基质中掺加手征体能改变基质的介电常数和磁导
率,从而对反射系数产生影响.-The use of different constitutive relations to study chiral metal coating absorbing characteristics, and compared. The results show that the chiral media as long as the electromagnetic parameters of the macro after the reunification, we can use different constitutive relations have been the same results, which revealed the constitutive relation of equivalence. The numerical results show that in the matrix of mixing matrix chiral physical change in dielectric constant and magnetic permeability, which have an impact on the reflection coefficient.
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Author: xuzhanxian |
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Description: This directory contains the following:
[fajd.m] The FAJD algorithm for finding the approximate general
(non-orthogonal) joint diagonalizer of a set of matrices.
[test.m] A routine to demonstrates the way to call FAJD after
generating a set of target-matrices.
[average_performance.m] A routine that compares the average
performance of FAJD with different fixed processing parameters.
[sir.m] A function that calculates the signal to interference ratio
(SIR) of a combined demixing-mixing matrix.
Contributed by Xi-Lin Li (e-mail: li-xl04@mails.tsinghua.edu.cn).
Comments, bug reports, questions and suggestions are welcome.
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Size: 3072 |
Author: 薛耀斌 |
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Description: Function Definition
- C: equalizer of MISO with N.L1 X 1
F: convolved mixing matrix with N X M, with length L2 of mixing
polynomial matrix, denoted by N.L2 X M
M: the number of inputs
N: the observations of system
L1: length of equalizer polynomial matrix
L2: length of mixing polynomial matrix
H: overall system with M.L X 1 vector
L: the length of overall system, L=L1+L2-1
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Author: s |
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Description: 下面是目录介绍
ADC---------ADC模数转换实验
ASM---------汇编程序实验
ASM_c-------汇编和C语言混合实验
CF----------CF读写实验
DcMotor-----直流电机实验
DMA——-----DMA数据传输实验
GPRS--------GPRS/GSM通讯实验
GPS---------GPS全球定位实验
IDE---------IDE测试实验
IIC---------IIC读写实验
IIS---------IIS音频实验
KeyScan-----行列式键盘扫描实验
Lcd---------TFT lcd显示实验
LED8X8------8x8 LED点阵实验
NandFlash---NandFlash读写实验
NorFlash----NorFlash读写实验
Pwm---------Pwm脉宽调制实验
RS485-------RS485通讯实验
Rtc---------Rtc实时时钟实验
StepMotor---步进电机控制实验
TFTP--------TFTP网络通讯实验
Timer_Interrupt---定时器中断实验
TouchPanel----触摸屏实验
UART--------串口通讯实验
uCOSII------uCOSII移植实验
USB_Device----USB deivce通讯实验
WatchDog-----看门狗实验-The following is a directory description
ADC--------- ADC ADC test
ASM--------- assembler experiment
ASM_c------- assembly and C language mixing experiment
CF---------- CF literacy test
DcMotor----- DC motor experiment
DMA------- DMA data transfer experiment
GPRS--------GPRS/GSM communication experiment
GPS--------- GPS Global Positioning Experiment
IDE--------- IDE Testing Laboratory
IIC--------- IIC literacy test
IIS--------- IIS audio test
KeyScan----- determinant keyboard scan experiment
Lcd--------- TFT lcd display experiments
LED8X8------ 8x8 LED dot matrix experiment
NandFlash--- NandFlash literacy test
NorFlash---- NorFlash literacy test
Pwm--------- Pwm PWM test
RS485------- RS485 communication experiment
Rtc--------- Rtc Real Time Clock Experiment
StepMotor--- stepper motor control experiment
TFTP-------- TFTP network communication experiment
Timer_Interrupt--- timer interrupt test
TouchPanel---- touch screen test
UART--------
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Author: asdfasdf |
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Description: 弱时频正交性条件下的混合矩阵盲估计Orthogonal frequency weak mixing matrix under the conditions of blind estimation-Orthogonal frequency weak mixing matrix under the conditions of blind estimation
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Author: soos1001 |
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Description: 二阶稀疏信号欠定盲分离，基于超平面法矢量的混合矩阵的估计-Second-order sparse underdetermined blind signal separation method based on hyperplane vector mixing matrix estimate
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Author: 李飞 |
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Description: In this interface, you can control the sources (type, frequency,
length, represented points), the mixture (elements of the mixing
matrix and nonlinears functions in the post nonlinears cases),
the different parameters of noise, the separating algorithm
(choice between two algorithms and associated parameters) and
the parameters of denoising.-All the algorithms simulated in this package have been designed
by Massoud BABAIE-ZADEH during his PhD thesis, prepared in the
Images and Signals Laboratory (LIS) of Institut National Polytechnique
de Grenoble (INPG), under the supervision of Christian JUTTEN.
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Author: 冯婷 |
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Description: 取一随机矩阵，作为信号混合的权矩阵，与三个模拟信号混合后，通过ICA算法能够完美地分离出三个源信号-Take a random matrix, as the right of the signal mixing matrix, with a mixture of three analog signals, the ICA algorithm can be perfectly isolated from the three source signals
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Author: 王泽林 |
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Description: AES加密过程是在一个4×4的字节矩阵上运作，这个矩阵又称为“体（state）”，其初值就是一个明文区块（矩阵中一个元素大小就是明文区块中的一个Byte）。（Rijndael加密法因支持更大的区块，其矩阵行数可视情况增加）加密时，各轮AES加密循环（除最后一轮外）均包含4个步骤：
1.AddRoundKey — 矩阵中的每一个字节都与该次回合金钥（round key）做XOR运算；每个子密钥由密钥生成方案产生。
2.SubBytes — 通过一个非线性的替换函数，用查找表的方式把每个字节替换成对应的字节。
3.ShiftRows — 将矩阵中的每个横列进行循环式移位。
4.MixColumns — 为了充分混合矩阵中各个直行的操作。这个步骤使用线性转换来混合每内联的四个字节。
最后一个加密循环中省略MixColumns步骤，而以另一个AddRoundKey取代。
-AES encryption process operates on a 44 byte matrix, this matrix is also known as " body (state), its initial value is a plaintext block (matrix element size is expressly block Byte ). (Rijndael encryption support larger blocks, the number of rows of the matrix, depending on the circumstances increase) encryption, each round of AES encryption cycle (except for the last one) contains four steps: 1.AddRoundKey- matrix a byte with the second leg (round key), key do XOR operation each sub-key generated by the key generation program. 2.SubBytes- replaced by a non-linear function using a lookup table of each byte is replaced by the corresponding byte. 3.ShiftRows- each row of the matrix is a cyclic shift. 4.MixColumns- to be sufficiently mixed in the matrix, the operation of the respective straight. This step uses the linear conversion by mixing the four bytes of each inline. The last encryption cycle MixColumns step is omitted, and substituted with another A
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Author: zhangyi |
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Description: 题名： ARM9嵌入式系统开发与实践(详细)
作者： 王黎明 ... [等] 编著
出版者： 北京航空航天大学出版社
日期： 2008
下面是目录介绍
ADC---------ADC模数转换实验
ASM---------汇编程序实验
ASM_c-------汇编和C语言混合实验
CF----------CF读写实验
DcMotor-----直流电机实验
DMA——-----DMA数据传输实验
GPRS--------GPRS/GSM通讯实验
GPS---------GPS全球定位实验
IDE---------IDE测试实验
IIC---------IIC读写实验
IIS---------IIS音频实验
KeyScan-----行列式键盘扫描实验
Lcd---------TFT lcd显示实验
LED8X8------8x8 LED点阵实验
NandFlash---NandFlash读写实验
NorFlash----NorFlash读写实验
Pwm---------Pwm脉宽调制实验
RS485-------RS485通讯实验
Rtc---------Rtc实时时钟实验
StepMotor---步进电机控制实验
TFTP--------TFTP网络通讯实验
Timer_Interrupt---定时器中断实验
TouchPanel----触摸屏实验
UART--------串口通讯实验
uCOSII------uCOSII移植实验
USB_Device----USB deivce通讯实验
WatchDog-----看门狗实验
-Title: ARM9 embedded system development and practice (detailed) Author: Wang Liming ... [et al.] Ed publisher: Beijing University of Aeronautics and Astronautics Press Date: 2008 Here is the Table of Contents Introduction ADC--------- the ADC analog-to-digital conversion experiments ASM--------- assembler experimental ASM_c------- assembler and C language mixing experiments CF---------- CF read and write experimental DcMotor---- of DC motors experiment DMA------- DMA data transmission experiment GPRS--------GPRS/GSM the communication experiment GPS--------- GPS global positioning experiment IDE--------- IDE Testing Laboratory IIC--------- IIC read and write experimental IIS--------- IIS audio experiments KeyScan----- determinant keyboard scan experiment Lcd--------- TFT lcd display experiments LED8X8------ 8x8 LED dot matrix experiments NandFlash--- the NandFlash read and write experiment NorFlash---- NorFlash read and write experimental Pwm--------- Pwm pulse width modulation experime
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Author: caoxiansheng |
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Description: fastica的源代码
有关数据的零均值处理，白化，以及寻找解混矩阵的实现代码-fastica data about the source code of zero mean processing, bleaching, and to find solutions to achieve mixing matrix code
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Author: 蓝雪 |
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Description: 二阶欠定盲分离程序，经典，完整，让您一目了然，请放心使用，原汁原味的matlab代码及详细的英文标注。-ack sobi_cp3
Second Order Blind Identification via Candecomp/Parafac order-3 (CP3)
to solve linear instantaneous Blind Source Separation (BSS).
sobi_cp3 allows to handle the exactly-determined, the over-determined and
several under-determined problems.
sobi_cp3 computes a set of K covariance matrices of the observed signals.
Then, the mixing matrix is estimated by joint-approximate-diagonalization (JAD)
of this set of matrices.
The JAD problem is solved by computing the CP3 decomposition of the third-order
tensor (3-way array) built by stacking the covariance matrices along the third
dimension.
It exploits the fact that JAD is a particular case of CP3 where the slices of
the tensor are symmetric, i.e., the mode-1 and mode-2 loading matrices
of the decomposition are identical.
Here the cp3 model is fitted by ignoring this symmetry, via an alternating
least squares (ALS) coupled with exact line search.
Thanks to powerful uniqueness properties of CP3, estimation of t
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Author: 李振涛 |
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Description: CCABSS - Blind Source Separation by Canonical Correlation Analysis
Y = CCABSS(X) is the BSS of X=A*S where S is a set of unknown source signals
and A is an unknown mixing matrix. The components in S are supposed to
be independent. Y is an estimate of S appart from permutation and scaling.
For mixed 1-D signals, X is 2-D. The first index refer to the different
components and the second index refers to the signal parameter (e.g. time)
For mixed images, X is 3-D where the first index refers to the different
mixed images and the second and third indeces are the spatial coordinates.
[Y W] = CCABSS(X) also gives the de-mixing matrix W, such that Y = W *X.-CCABSS - Blind Source Separation by Canonical Correlation Analysis
Y = CCABSS(X) is the BSS of X=A*S where S is a set of unknown source signals
and A is an unknown mixing matrix. The components in S are supposed to
be independent. Y is an estimate of S appart from permutation and scaling.
For mixed 1-D signals, X is 2-D. The first index refer to the different
components and the second index refers to the signal parameter (e.g. time)
For mixed images, X is 3-D where the first index refers to the different
mixed images and the second and third indeces are the spatial coordinates.
[Y W] = CCABSS(X) also gives the de-mixing matrix W, such that Y = W *X.
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Author: harish bsv |
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Description: 灰度梯度共生矩阵 H
归一化灰度梯度矩阵 H_basic
小梯度优势 T1
大梯度优势 T2
灰度分布的不均匀性 T3
梯度分布的不均匀性 T4
能量 T5
灰度平均 T6
梯度平均 T7
灰度均方差 T8
梯度均方差 T9
相关 T10
灰度熵 T11
梯度熵 T12
混合熵 T13
惯性 T14
逆差矩 T15-GGCM H normalized gray gradient matrix H_basic small advantage T1 gradient big advantage T2 gradient gray uneven distribution of T3 gradient uneven distribution of energy T5 gray T4 average T6 average gradient gray T7 average gradient T8 variance variance T9 were related to T10 T11 gradient gray entropy entropy of mixing entropy T12 T13 inertia moment T15 T14 deficit
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Author: 马奔 |
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Description: 盲源分离中的EASI算法，程序中提供源信号（源信号均为次高斯信号），固定的信道混合矩阵，EASI分离算法。EASI算法为定步长EASI算法，步长固定。程序中包含PI值收敛曲线程序。整体程序可以产生源信号图、混合信号图、解混信号图、PI值收敛曲线。(The EASI algorithm in the blind source separation provides the source signal (the source signal is the next Gaussian signal), the fixed channel mixing matrix, and the EASI separation algorithm. The EASI algorithm is a fixed step EASI algorithm, fixed in steps. The program contains the PI value convergence curve program. The overall program can produce the source signal map, mixed signal map, deconvolution signal graph, PI value convergence curve.)
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Author: sabermaple
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