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FFT
- Matlab中的fft分析含噪声的信号，其中有直接FFT，时域同步平均后FFT，频域同步平均后FFT-Matlab' s fft of noisy signals, which have a direct FFT, time-domain synchronous averaging the FFT, frequency domain averaged FFT synchronization
FFT_Analysis
- Matlab中的fft分析含噪声的信号，其中有直接FFT，时域同步平均后FFT，频域同步平均后FFT-Matlab s fft analysis with noise signals, which have a direct FFT, time-domain synchronous average, after the FFT, frequency domain synchronization for after averaging FFT
slidefilter
- Sliding Sum Averaging Filter Smoothes data by sliding it past itself, one sample at a time, and summing. The length of the output is the same as the length of the input. The output will be normalized. Equivalent to a moving average (lowpass
example_1_dc
- // This program provides simple DC motor control using the PCA 8-bit PWM Mode. // The ADC is used to read the potentiometer voltage on P0.6. The ADC uses // polled mode and 64 sample averaging. The 8-bit PWM is configured to operate // at 24 kH
Correlation_and_convolution
- About correlation. In signal processing, cross-correlation is a measure of similarity of two waveforms as a function of a time-lag applied to one of them. This is also known as a sliding dot product or inner-product. It is commonly used to search a l
crosscorelation
- In signal processing, cross-correlation is a measure of similarity of two waveforms as a function of a time-lag applied to one of them. This is also known as a sliding dot product or inner-product. It is commonly used to search a long duration signal
averaging2
- averaging of time domain signal.
fractal_image
- 2 M-files are being uploaded for image Partitioning & image averaging. Some example images are attached. These Programme also Calculate time taken in Partitioning & image averaging.-2 M-files are being uploaded for image Partitioning & image averagin
animMPCPDisplay
- matlab code for averaging data time series
animMPCPresidual
- matlab code for averaging data time series
animMPWPresidual
- matlab code for averaging data time series
H-02prgrams
- matlab code for averaging data time series
kriging
- 该方法在数学上可对所研究的对象提供一种最佳线性无偏估计(某点处的确定值)的方法。它是考虑了信息样品的形状、大小及与待估计块段相互间的空间位置等几何特征以及品位的空间结构之后，为达到线性、无偏和最小估计方差的估计，而对每一个样品赋与一定的系数，最后 进行加权平均来估计块段品位的方法。但它仍是一种光滑的内插方法 在数据点多时，其内插的结果可信度较高 。-The method of mathematical research object to provide a best linear unbias
computerwork_2
- 2. 设 是窄带信号，定义 是在 区间上均匀分布的随机相位。 是寬带信号，它是一个零均值、方差为1的白噪音信号e(n)激励一个线性滤波器而产生，其差分方程为 。 1） 计算 和 各自的自相关函数，并画出其函数图形。根据此选择合适的延时，以实现谱线增强。 2） 产生一个 序列。选择合适的 值。让 通过谱线增强器。画出输出信号 和误差信号e(n)的波形，并分别与 和 比较。 -Computer Experiments: 1. Consider an AR process x
TSA
- 时域同步平均法，在降噪上有很明显的帮助TSA-Time-domain synchronous averaging method, the noise has obviously help
IMCRA111
- IMCRA(Improved?Minima Controlled Recursive Averaging，IMCRA)，它们虽然保证了噪声谱估计的准确性，但在追踪带噪语音平滑功率谱最小值时采用了固定时间窗，因此，在噪声突变的情况下，估计的噪声谱存在很长的延时。(IMCRA, Although they ensure the accuracy of noise spectrum estimation, they use a fixed time window to track the minimu