Description: MIMO无线传输 无线传输 无线传输 -MIMO transmission model, JAKAFANI Quasi orthogonal space time block codes with four transmit and one receive antenans over flat fading channel with maximum likelihood detector (ML)
Platform: |
Size: 544768 |
Author:albert |
Hits:
Description: 电子书
Two features of "Processing Random Data" differentiate it from other similar books: the focus on computing the reproducibility error for statistical measurements, and its comprehensive coverage of Maximum Likelihood parameter estimation techniques. The book is useful for dealing with situations where there is a model relating to the input and output of a process, but with a random component, which could be noise in the system or the process itself could be random, like turbulence. Parameter estimation techniques are shown for many different types of statistical models, including joint Gaussian. The Cramer-Rao bounds are described as useful estimates of reproducibility errors. Finally, using an example with a random sampling of turbulent flows that can occur when using laser anemometry, the book also explains the use of conditional probabilities.-Processing random data
Two features of "Processing Random Data" differentiate it from other similar books: the focus on computing the reproducibility error for statistical measurements, and its comprehensive coverage of Maximum Likelihood parameter estimation techniques. The book is useful for dealing with situations where there is a model relating to the input and output of a process, but with a random component, which could be noise in the system or the process itself could be random, like turbulence. Parameter estimation techniques are shown for many different types of statistical models, including joint Gaussian. The Cramer-Rao bounds are described as useful estimates of reproducibility errors. Finally, using an example with a random sampling of turbulent flows that can occur when using laser anemometry, the book also explains the use of conditional probabilities. Platform: |
Size: 4691968 |
Author:november |
Hits:
Description: 常规DOA谱估计music算法在多径环境下失效，SVD算法利用最大特征值对应的特征矢量重新构造奇异值矩阵，可以成功估计相干信号。-Conventional music spectrum estimation algorithm for DOA in multipath environment, failure, SVD algorithm using the maximum eigenvalue of the feature vector corresponding to re-construct singular value matrix, can be successfully estimated coherent signal. Platform: |
Size: 1024 |
Author:ll |
Hits:
Description: 本演示程序分别就线性，判决反馈，和最大似然估计均衡器的进行了误码率性能仿真。-This demo program in respect of linear, decision feedback, and the maximum likelihood estimation equalizer BER performance simulation carried out. Platform: |
Size: 102400 |
Author:miaoyi |
Hits:
Description: 威布尔模型的参数估计方法_极大似然法,对这方面研究人有帮助-Weibull model parameters estimation method _ maximum likelihood method, studies were helpful in this regard Platform: |
Size: 116736 |
Author:zz |
Hits:
Description: It is a program for Maximum likelihood equalization for space time block codes in MIMO systems Platform: |
Size: 7168 |
Author:bunny |
Hits:
Description: 【1】随机序列产生程序
【2】白噪声产生程序
【3】M序列产生程序
【4】二阶系统一次性完成最小二乘辨识程序
【5】实际压力系统的最小二乘辨识程序
【6】递推的最小二乘辨识程序
【7】增广的最小二乘辨识程序
【8】梯度校正的最小二乘辨识程序
【9】递推的极大似然辨识程序
【10】Bayes辨识程序
【11】改进的神经网络MBP算法对噪声系统辨识程序
【12】多维非线性函数辨识程序的Matlab程序
【13】模糊神经网络解耦Matlab程序
【14】F-检验法部分程序
-【1】 【2-random sequence generation process white noise generation process】 【3】 M sequence generation process 【4】 to complete a one-time second-order system least-squares identification procedure 【5】 actual pressure system least-squares identification procedure 【6】 Delivery Push the least squares identification procedure augmented 【7】 【8】 least square identification procedures for gradient correction least square identification procedure 【9】 Recursive maximum likelihood identification procedures 【10】 【11】 Bayes identification procedures Improved neural network algorithm MBP noise system identification procedure 【12】 multi-dimensional nonlinear function identification program Matlab program 【13】 fuzzy neural network decoupling Matlab program 【14】 F-test part of the program Platform: |
Size: 7168 |
Author:jshuska |
Hits:
Description: The demo shows two nonlinear interference cancellation methods - Zero-Forcing and Minimum-Mean-Square-Error - with symbol cancellation and compares their performance with the Maximum-Likelihood optimum receiver. Platform: |
Size: 71680 |
Author:KidQn |
Hits:
Description: 卡尔曼滤波是信号处理的重要工具，而极大似然估计是概率论的重要思想，两者结合会解决一系列类似的问题-Kalman filtering is an important tool for signal processing, while the maximum likelihood estimation is the important thinking of the probability theory, a combination of both will solve a series of similar problems Platform: |
Size: 331776 |
Author:xuna |
Hits:
Description: 模式识别实验验程序
极大似然估计和Fisher线形判别分析-Experimental test procedures for pattern recognition maximum likelihood estimation and Fisher linear discriminant analysis Platform: |
Size: 48128 |
Author:肖达 |
Hits:
Description: 通信仿真，二元位信号通过加性高斯白噪声的信道，经过匹配滤波，最大后验概率和最大似然概率检测比较-Communication simulation, binary bits signals through the additive gaussian white noise, through the channel is matched filtering, maximum a posteriori probability and the maximum likelihood detection probability Platform: |
Size: 2048 |
Author:王峰 |
Hits:
Description: In statistics, an expectation-maximization (EM) algorithm is a method for finding maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. EM is an iterative method which alternates between performing an expectation (E) step, which computes the expectation of the log-likelihood evaluated using the current estimate for the latent variables, and a maximization (M) step, which computes parameters maximizing the expected log-likelihood found on the E step. These parameter-estimates are then used to determine the distribution of the latent variables in the next E step.-In statistics, an expectation-maximization (EM) algorithm is a method for finding maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. EM is an iterative method which alternates between performing an expectation (E) step, which computes the expectation of the log-likelihood evaluated using the current estimate for the latent variables, and a maximization (M) step, which computes parameters maximizing the expected log-likelihood found on the E step. These parameter-estimates are then used to determine the distribution of the latent variables in the next E step.
Platform: |
Size: 2048 |
Author:loossii |
Hits:
Description: 该程序源码中包括了各种典型分布的二维数据的自动生成，二维概率密度函数的极大似然估计和窗函数估计，bayes分类器的设计和分类器错误率的多种方法估计-The program includes a variety of typical source distribution of the automatic generation of two-dimensional data, two-dimensional probability density function of the maximum likelihood estimation and window function estimation, bayes classifier design and classifier error rate estimated a variety of ways Platform: |
Size: 9216 |
Author:聂雨桐 |
Hits:
Description: 请录制语音信号集 （不能少于五个语音），然后根据最大似然估计方法，利用MATLAB设计一识别程序，并实现。-Please record a voice signal is set (not less than five voice), then maximum likelihood estimation method, using MATLAB to design a recognition program, and implementation. Platform: |
Size: 2069504 |
Author:Dean |
Hits:
Description: 牛顿拉夫森法用来解决极大似然估计的问题。很好用。-Newton La Fusen method to solve the problem of maximum likelihood estimation. Good use. Platform: |
Size: 430080 |
Author:jianghan |
Hits:
Description: urbo码是1993年法国人Berrou提出的一种新型编码方法。它巧妙的将卷积码和随机交织器结合在一起；同时，采用软输出迭代译码来逼近最大似然译码-urbo code is 1993 French Berrou proposed a new encoding method. It is clever to convolutional codes and random interleaver together the same time, the use of soft-output iterative decoding to approximate the maximum likelihood decoding Platform: |
Size: 62464 |
Author:wangzhi |
Hits:
Search - maximum likelihood