Description: 这个是关于OFDM系统的信道估计的算法的两种方法，分别是OFDM的最小二乘和最小均方误差估计的仿真程序代码-the OFDM system is on the channel estimation algorithm of the two methods OFDM are the least squares and minimum mean square error estimate of simulation code Platform: |
Size: 5120 |
Author:周洁 |
Hits:
Description: We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation,
phase-shift keying, and pulse amplitude modulation
communications systems.We study the performance of a standard
CFO estimate, which consists of first raising the received signal to
the Mth power, where M is an integer depending on the type and
size of the symbol constellation, and then applying the nonlinear
least squares (NLLS) estimation approach. At low signal-to noise
ratio (SNR), the NLLS method fails to provide an accurate CFO
estimate because of the presence of outliers. In this letter, we derive
an approximate closed-form expression for the outlier probability.
This enables us to predict the mean-square error (MSE) on CFO
estimation for all SNR values. For a given SNR, the new results
also give insight into the minimum number of samples required in
the CFO estimation procedure, in order to ensure that the MSE
on estimation is not significantly affected by the outliers. Platform: |
Size: 1265664 |
Author:吴大亨 |
Hits:
Description: Beamforming thesis describing Study of a various Beamforming Techniques And Implementation of the Constrained Least Mean Squares (LMS) algorithm for Beamforming Platform: |
Size: 770048 |
Author:anik |
Hits:
Description: System identification with adaptive filter using full and partial-update Generalised-Sideband-Decomposition Least-Mean-Squares Platform: |
Size: 4096 |
Author:Peter Tiong |
Hits:
Description: System identification with adaptive filter using full and partial-update Least-Mean-Squares -System identification with adaptive filter using full and partial-update Least-Mean-Squares Platform: |
Size: 4096 |
Author:Peter Tiong |
Hits:
Description: System identification with adaptive filter using full and partial-update Normalised-Least-Mean-Squares
Platform: |
Size: 5120 |
Author:Peter Tiong |
Hits:
Description: System identification with adaptive filter using full and partial-update Transform-Domain Least-Mean-Squares-System identification with adaptive filter using full and partial-update Transform-Domain Least-Mean-Squares Platform: |
Size: 4096 |
Author:Peter Tiong |
Hits:
Description: 这是一篇关于椭圆检测的文章:对于做人脸识别,模式识别的同行应该会有所帮助.找了好久,才下到,上传来共享下.-abstract:The Hough transformation can detect straight lines in an edge-enhanced picture, however its extension torecover ellipses
requires too long a computing time. This correspondence proposes a
modified method which utilizes two properties of an ellipse in such a
way that it iteratively searches for clusters in two different parameter
spaces to find almost complete ellipses, then evaluates their parameters
by the least mean squares method. Platform: |
Size: 1918976 |
Author:华瑞娟 |
Hits:
Description: 均衡技术是克服码间干扰(Inter-Symbol Interference,ISI)的有效措施,由于信道特性的随机性与时变性,实际中消除码间干扰最常用的是自适应均衡器。本文对基于最小均方(Least Mean Squares,LMS)算法和递推最小二乘(Recursive Least Squares,RLS)算法的自适应均衡器进行仿真研究,分析了信道特性与设计参数对自适应均衡器的收敛速度与稳态性能的影响。
-Equalization technique is to overcome inter-symbol interference (Inter-Symbol Interference, ISI) and effective measures, due to the randomness of the channel characteristics with the variability in practice to eliminate inter-symbol interference is the most commonly used adaptive equalizer. In this paper, based on minimum mean-square (Least Mean Squares, LMS) algorithm and recursive least squares (Recursive Least Squares, RLS) algorithm is adaptive equalizer simulation studies to analyze the channel characteristics and design parameters of the adaptive equalizer convergence speed and steady-state performance. Platform: |
Size: 1024 |
Author:xieliwei |
Hits:
Description: Least mean squares (LMS) algorithms is a type of adaptive filter used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean squares of the error signal (difference between the desired and the actual signal). It is a stochastic gradient descent method in that the filter is only adapted based on the error at the current time Platform: |
Size: 719872 |
Author:hopu chan |
Hits:
Description: matlab的各种自适应仿真分析。。自适应信息处理的算法、方案繁多，究其实质可归纳为遵循最小均方误差(Least Mean Square，LMS)准则及最小二乘(Least Square，LS)准则两大类，其他算法大多是这两种算法的演进。-matlab simulation analysis of various adaptive. . Adaptive information processing algorithms, a variety of plans, their essence can be summarized as follows the minimum mean square error (Least Mean Square, LMS) criterion and least squares (Least Square, LS) criteria for two categories, most of the two other algorithms kind of algorithm evolution. Platform: |
Size: 2366464 |
Author:杨学海 |
Hits:
Description: LMS: Least mean squares (LMS) algorithms is a type of adaptive filter used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean squares of the error signal (difference between the desired and the actual signal) Platform: |
Size: 3072 |
Author:Sam |
Hits:
Description: LMS: Least mean squares (LMS) algorithms is a type of adaptive filter used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean squares of the error signal (difference between the desired and the actual signal) Platform: |
Size: 5120 |
Author:Sam |
Hits:
Description: Least mean squares (LMS) algorithms is a type of adaptive filter used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean squares of the error signal (difference between the desired and the actual signal) Platform: |
Size: 114688 |
Author:Sam |
Hits:
Description: Inter-symbol interference if not taken care off may
cause severe error at the receiver and the detection of signal becomes
difficult. An adaptive equalizer employing Recursive Least Squares
algorithm can be a good compensation for the ISI problem. In this
paper performance of communication link in presence of Least Mean
Square and Recursive Least Squares equalizer algorithm is analyzed.
A Model of communication system having Quadrature amplitude
modulation and Rician fading channel is implemented using
MATLAB communication block set. Bit error rate and number of
errors is evaluated for RLS and LMS equalizer algorithm, due to
change in Signal to Noise Ratio (SNR) and fading component gain in
Rician fading Channel. Platform: |
Size: 400384 |
Author:pravin jadhav |
Hits:
Description: Least mean squares (LMS) algorithms are a class of adaptive filter used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean squares of the error signal (difference between the desired and the actual signal) Platform: |
Size: 102400 |
Author:Gowri |
Hits:
Search - least mean squares