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sinecostas
- 用costas环检测淹没在噪声和未知任何先验参数的正弦信号检测-with Costas Loop Detection drowned in the noise and any a priori unknown parameters of sinusoidal signal detection
RobustadaptiveKalmanfilteringwithunknowninputs
- The standard optimum Kalman filter demands complete knowledge of the system parameters, the input forcing functions, and the noise statistics. Several adaptive methods have already been devised to obtain the unknown information using the measur
AdaptiveLineEnhancer
- This demonstration illustrates the application of adaptive filters to signal separation using a structure called an adaptive line enhancer (ALE). In adaptive line enhancement, a measured signal x(n) contains two signals, an unknown signal of in
LMSfilter
- 假设一个接收到的信号为：x(t)=s(t)+n(t), 其中s(t)=A*cos(wt+a), 已知信号的频率w=1KHz， 而信号的幅度和相位未知，n(t)是一个服从N(0,1)分布的白噪声。为了利用计算机对信号进行处理， 将信号按10KHz的频率进行采样。 通过对x(t)进行LMS自适应信号处理，从接收信号中滤出有用信号s(t). 在未知信号频率的情况下，通过对x(t)进行LMS自适应信号处理，从接收信号中滤出有用信号s(t). -Assuming a received
DSSS_enhanced_with_a_coarse_time_synchronization_
- The .m file simulates a Spread-Spectrum Modulation Trx/Rcx system, in which, the phase of the pseudo-random sequence generated in the transmitter and used to encode the data stream is unknown a priory at the receiver.A parallel search strategy is emp
1
- Cognitive radio frequency spectrum detection-The spectrum sensing of a wideband frequency range is studied by dividing it into multiple subbands. It is assumed that in each subband either a primary user (PU) is active or absent in a additive white
evar
- 假设被噪声污染的信号服从高斯分布,估计高斯噪声的方差.-A signal corrupted by a Gaussian noise with unknown variance. It is often of interest to know more about this variance. The function thus returns an estimated variance of the additive noise.
SVSLMS
- 本程序提出了变步长自适应滤波算法的步长调整原则:即在初始收敛阶段或未知系统参数发生变化时,步长应比较大,以便有较快的收 敛速度和对时变系统的跟踪速度 而在算法收敛后,不管主输入端干扰信号v ( n) 有多大,都应保持很小的调整步长以达到很小的稳态失调噪声. 根据变步长公式编的程序，很有参考价值. -This procedure, a variable step adaptive filter algorithm step adjustment principle: that in the
energydetectionofunknownsignalsoverfading
- energy detection of unknown signals over noise and fading
fecgm
- 独立成份分析（ＩＣＡ）以及ｗｉｎｎｅｒ滤波 Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S + N where o A is an unknown n x m matrix with full rank.
ABlindEstimationAlgorithmforPNSequenceinDSSSSignal
- 这是一篇很好的有关信道估计的文章， 可以用来快速的了解信道估计的基本内容-In this paper, a method for fast blind estimation of DS-SS signal is proposed which aims at the Direct-Sequence Spread- Spectrum (DS-SS) signals with parameters unknown. Considering the characteristic th
system_identification_RELS001
- 系统参数辨识，用增广最小二乘算法实现。对书中的程序进行了改进：由于噪声是未知的，虽然我们模拟了系统的随机白噪声，但进行辨识时必须对噪声进行估计，见程序45行和53行。-System parameter identification, with the extended least squares algorithm. Procedures for improving the book: Because the noise is unknown, although we simulate a sy
mic1
- There are four major types of adaptive filtering configurations adaptive system identification, adaptive noise cancellation, adaptive linear prediction, and adaptive inverse system. All of the above systems are similar in the implementation of the al
BID-of-Multichannel
- 盲辨识的模糊和多路冷杉完美的图像恢复 乔治·吉昂奈吉斯，研究员，美国，和罗伯特·希斯，小，成员，美国-Despite its practical importance in image processing and computer vision, blind blur identification and blind image restoration have so far been addressed under restrictive assumptions such a
SVDTLS
- 用Matlab仿真实现最小二乘法和总体最小二乘法估计 假设仿真的观测数据 产生，其中 为0均值， 单位方差的高斯白噪声，取n=1,2,....128。 试用TLS，取AR阶数为4，估计AR参数 和正弦波频率；再用SVD-TLS ，估计AR参数 和正弦波频率。 (1)、在仿真中，AR阶数取为4和6。 (2)、执行SVD-TCS时，AR未知。仿真运行至少二十次。 -Simulation using Matlab and the overall least squares leas
detect_pf_unknow_WGN
- 阵列信号处理白色高斯噪声下检测未知参数信号的概率-The probability of detection signals of the unknown parameters in the array signal processing white Gaussian noise
deblurring_demo-1.0
- Bayesian Deblurring with Integrated Noise Estimation-Bayesian Deblurring with Integrated Noise Estimation Conventional non-blind image deblurring algorithms involve natural image priors and maximum a-posteriori (MAP) estimation. As a consequenc
SplitBregmanTVdenoising1
- 基于Split Bregman TV方法的一种图像去噪/图像恢复算法，对于未知的噪声具有很好地处理效果。-An image-based method of de-noising Split Bregman TV/image restoration algorithm, for unknown noise with good treatment effect.
zedboard_master_XDC_RevC_D_v3
- 在这个实验中，使用Mathworks HDL Coder工具产生一个LMS噪声消除的滤波器。HDL coder会基于Simulink模型生成RTL模型封装进IP核。这个滤波器可以自适应地将未知的噪声滤除，输出处理后的信号。(In this exeriment, the Mathworks HDL Coder tool is used to generate a LMS noise elimination filter. HDL coder generates the RTL model base
1
- 一篇关于变分贝叶斯解决噪声参数未知的论文代码，噪声分布使用了逆威沙特分布构建(A paper code about solving the unknown noise parameters with variable decibel Bayes. The noise distribution is constructed with inverse wissaud distribution)