Description: LMS算法MatLab实现
LMS自适应滤波器是使滤波器的输出信号与期望响应之间的误差的均方值为最小，因此称为最小均方（LMS）自适应滤波器。-MatLab realize LMS algorithm LMS adaptive filter is to filter the output signal in response to and expectations of the error between the mean square value of the smallest, so called the least mean square (LMS) adaptive filter. Platform: |
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Author:jj |
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Description: LMS自适应滤波器是使滤波器的输出信号与期望响应之间的误差的均方值为最小，因此称为最小均方（LMS）自适应滤波器。-LMS adaptive filter is to filter the output signal in response to and expectations of the error between the mean square value of the smallest, so called the least mean square (LMS) adaptive filter. Platform: |
Size: 47104 |
Author:jj |
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Description: 自适应滤波器的特点是自动调节自身的冲激响应,达到最优滤波,此算法适用于平稳和非平稳随机信号,并且不要求知道信号和噪声的统计特性。-Adaptive filter is characterized by automatic adjustment of its own impulse response, the optimal filtering, this algorithm applied to a smooth and non-stationary random signal, and does not demand to know the signal and noise is investigated. Platform: |
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Author:xurui |
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Description: 由于自适应滤波器组的频率响应匹配于信号的统计特性,所以能够得到更为有效的信号分解. 文中根据信号的统计特性,按照低通子带能量最大化的原理设计自适应滤波器组. 结合自适应滤波器组和传统的阈值方法,得到一种更为有效的去噪方法. 实验结果表明,与相同长度的标准滤波器相比,新方法得到了更大的信噪比改善.-Adaptive filter banks as a result of the frequency response to match the statistical properties of the signal, it can be more effective decomposition of the signal. According to the statistical properties of signals, in accordance with the low-pass sub-band energy to maximize the principle of the design of adaptive filters. combination of adaptive filter and the traditional threshold methods, to be a more effective de-noising method. The experimental results show that the standard with the same filter length, the new methods to improve signal to noise ratio greater. Platform: |
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Author:gg |
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Description: In almost all analyzes of the least mean-square (LMS)
finite impulse response (FIR) adaptive algorithm, it is assumed that
the length of the adaptive filter is equal to that of the unknown
system impulse response. However, in many practical situations,
a deficient length adaptive filter, whose length is less than that of
the unknown system, is employed, and analysis results for the sufficient
length LMS algorithm are not necessarily applicable to the
deficient length case. Platform: |
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Author:behrouz |
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Description: 信道的频率响应是时变的，设计最佳的固定的解调滤波是不可能的，因此，需要一种能补偿或减少接收信号中ISI的方法，这种ISI补偿方法称为均衡方法。
自适应均衡技术能够用来抵消由于信道带限或时间色散所导致的码间干扰，可以使通信系统更有效地利用信道带宽。
-Channel frequency response is time-varying, the best fixed design demodulation filter is impossible, therefore, need to be able to receive compensation or reduce the signal in the ISI method, the ISI compensation is called a balanced approach. Adaptive equalization techniques can be used to offset the channel band-limited or time dispersion caused by the inter-symbol interference can make communication systems more efficient use of channel bandwidth. Platform: |
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Author:高露洁 |
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Description: 自适应滤波器是一种参数可自适应调整的有限冲激响应(FIR)数字滤波器，具有非递归结构形式。介绍了自适应滤波器的基本原理，用LMS自适应算法来仿真，得到LMS算法在自适应滤波中的收敛特性。-Adaptive filter is an adaptive adjustment of parameters can be finite impulse response (FIR) digital filter, with a non-recursive structure. Describes the basic principles of adaptive filter with LMS adaptive algorithm simulation, LMS algorithm in adaptive filtering convergence characteristics. Platform: |
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Author:Ling Li |
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Description: 用dsp实现自适应滤波器算法，自适应滤波是仅需对当前观察的数据作处理的滤波算法。它能自动调节本身冲激响应的特性，或者说自动调节数字滤波器的系数，以适应信号变化的特性，从而达到最佳滤波。由于自适应滤波不需要关于输入信号的先验知识，计算量小，特别适用于实时处理，近年来得到广泛应用，如用于脑电图和心电图测量、噪声抵消、扩频通信及数字电话等。-Dsp to achieve the adaptive filter algorithm, the adaptive filter is a filter that only the current observation data processing algorithm. It can automatically adjust itself to the impulse response characteristics, or automatically adjust the digital filter coefficients to adapt to the characteristics of the signal changes to achieve the best filter. Adaptive filter does not require a priori knowledge about the input signal, the small amount of calculation, especially real-time processing has been widely used in recent years, such as EEG and ECG measurement, noise cancellation, spread spectrum communications, and digital telephone . Platform: |
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Author:车 |
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Description: LMS自适应滤波器是使滤波器的输出信号与期望响应之间的误差的均方值为最小，因此称为最小均方（LMS）自适应滤波器，这个是LMS在matlab的m文件，使用方便-LMS adaptive filter is the mean square value of the minimum error between the filter output signal and desired response, so called least-mean-square (LMS) adaptive filter, the LMS in matlab m-files,convenient Platform: |
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Author:Freelance |
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Description: LMS自适应滤波器是使滤波器的输出信号与期望响应之间的误差的均方值为最小，因此称为最小均方（LMS）自适应滤波器。-LMS adaptive filter so that the filter output signal and the expected response the error between the minimum mean square value, so called minimum mean square (LMS) adaptive filter. Platform: |
Size: 1024 |
Author:张立峰 |
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Description: 有源自适应噪声的最常用算法，该算法是基于滤波器的输出信号与期望响应之间的误差的均方值为最小。-Active adaptive noise most commonly used algorithm, which is based on the error between the filter output signal and the desired response minimum mean-square value. Platform: |
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Author:姜鸿羽 |
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Description: 1、产生信号，两个实正弦信号的叠加，幅度分别为2、4、1、3；混入均值为0、方差为1的白噪声。采用自适应滤波器对其进行去噪。
2.产生信号，为两个实正弦信号的叠加，其幅度均为4，混入均值为0、方差为1的白噪声。采用有限脉冲响应法设计一个维纳滤波器估计信号 ，并求最小均方误差。
3.产生高斯分布的白噪声w(n)，自行给定一个5阶AR模型，让该白噪声通过这个AR模型，得到输出信号x(n），再估计x(n）的AR模型数，比较估计的结果和原来给定的AR模型的参数。-A signal to be generated, the superposition of two real sinusoidal signals, amplitude, respectively 2,4,1,3 mixed with mean 0 and variance 1 white noise. Noising using adaptive filter them. (2) generate signals as a superposition of two real sinusoidal signal whose amplitude was 4, mixed with mean 0 and variance 1 white noise. The finite impulse response method to design a Wiener filter estimate signal, and for the minimum mean square error. 3 Gaussian white noise generated w (n), given a five self-order AR model, so that the white noise through the AR model, get the output signal x (n), and then estimate x (n) the number of AR model, Compare the results and the original estimate given by the AR model parameters. Platform: |
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Author:chen |
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Description: This paper presents the modeling and implementation of a three-phase DSTATCOM (Distribution Static
Compensator) using STF (Self Tuning Filter) based IRPT (Instantaneous Reactive Power Theory) control
algorithm for power quality improvement. It is used for harmonics elimination, load balancing and
reactive power compensation at distorted PCC (Point of Common Coupling) voltages under nonlinear
loads. An adaptive fuzzy logic controller is used to control the dc bus voltage of VSC (Voltage Source
Converter) based DSTATCOM to improve the response and to reduce the overshoot and undershoot of
traditiona Platform: |
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Author:yangs |
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Description: This paper proposes an effective control scheme
for three-phase three-wire (3P3W) active power filter using
neural-based harmonic identification scheme. To achieve
excellent steady state and dynamic response, the feedback
control plus feed-forward control structures is utilized in the
proposed control algorithms. The steady-state error minimization
is achieved by the feedback loop, where the proportional
integral regulators were adopted in d-axis and
q-axis of the synchronous rotating reference frame synchronized
with grid voltages by using the phase-locked loop. The
adaptive linear combiners are utilized in the feed-forward
loop, which serves the purpose of load disturbance rejection,
and it significantly enhances dynamic performance of active
power filter (APF). Platform: |
Size: 1275904 |
Author:samir |
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Description: 信道均衡的MATLAB程例，是一个很好的例子，对于做通信信道仿真研究的就有较高的参考和使用价值。(In this example we have a typical channel equalization scenario. We want
to estimate the transmitted sequence with 4-QAM symbols. In
order to accomplish this task we use an adaptive filter with N coefficients
The procedure is:
1) Apply the originally transmitted signal distorted by the channel plus
environment noise as the input signal to an adaptive filter.
In this case, the transmitted signal is a random sequence with 4-QAM
symbols and unit variance. The channel is a multipath complex-valued
channel whose impulse response is h = [1.1+j*0.5, 0.1-j*0.3, -0.2-j*0.1]^T
In addition, the environment noise is AWGN with zero mean and
variance 10^(-2.5).
2) Choose an adaptive filtering algorithm to govern the rules of coefficient
updating.) Platform: |
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Author:ZJL0110
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Search - adaptive filter response