Description: 1．用Matlab产生正弦波,矩形波,以及白噪声信号，并显示各自时域波形图
2．进行FFT变换，显示各自频谱图，其中采样率，频率、数据长度自选
3．做出上述三种信号的均方根图谱,功率图谱,以及对数均方根图谱
4．用IFFT傅立叶反变换恢复信号，并显示恢复的正弦信号时域波形图
-1. Using Matlab generated sine wave, rectangular wave, as well as the white noise signal, and display their respective time-domain waveform of Figure 2. FFT to transform, showing their frequency spectrum, including sampling rate, frequency, data length of 3-on-demand. Made of the three signals in root-mean-square maps, power maps, as well as the number of root-mean-square map 4. Fourier Transform IFFT with the restoration of signals, and displays the sinusoidal signal the resumption of time-domain waveform Platform: |
Size: 4096 |
Author:白杨 |
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Description: 本实验要求编写一个计算压缩-解压缩图像的均方根误差、均方信噪比的程序。该程序是一个通用程序。编写程序产生图示的结果。使用上面的保真度准则程序计算可视信息的损失特性。-Prepared in this experiment, a calculation of compression- decompression of the root-mean-square error of image, mean square signal to noise ratio of the procedure. The procedure is a common procedure. Picture shows the preparation of the results of procedures. The use of the above criteria for the fidelity of calculated loss characteristics of visual information. Platform: |
Size: 95232 |
Author:jhm |
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Description: 采用MATLAB编程，产生一个16QAM基带信号，并进行实数倍插值计算。要求符号率为1 MSymbol/s，采用均方根升余弦滤波成形，滚降系数=0.5。产生{…1，0，1，1，…}的伪随机序列，经过映射、4倍成形滤波、FIR半带滤波、实数倍内插滤波，最后输出4.315倍时域/频域响应。给出信号序列经过各级滤波的时域、频域结果-Using MATLAB programming, resulting in a 16QAM baseband signal, and the real multiples of the interpolation calculation. The requirements of symbol rate 1 MSymbol/s, the root mean square raised cosine filter shape, roll-off factor = 0.5. Generate {1,0,1,1, ...} of the pseudo-random sequence, mapping, four times the shaping filter, FIR half-band filter, in fact, several times interpolation filter, the final output of 4.315 times the time domain/frequency domain response. Given the signal sequence through all levels of filtering the time domain, frequency domain results Platform: |
Size: 239616 |
Author: |
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Description: In this paper the analysis of the compression process was performed by comparing the compressed signal against the original signal. To do this the most powerful speech analysis and compression techniques such as Linear Predictive Coding (LPC) and Discrete Wavelet Transform (DWT) was implemented using MATLAB. Here nine samples of spoken words are collected from different speakers and are used for implementation. The results obtained from LPC were compared with other compression technique called Discrete Wavelet Transform. Finally the results were evaluated in terms of compressed ratio (CR), Peak signal-to-noise ratio (PSNR) and Normalized root-mean square error (NRMSE).The result shows that DWT performance was better for these samples than the LPC method. Platform: |
Size: 147456 |
Author:Ambika |
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Description: 自己用的时域特征提取方式，包含均值，均方根值，歪度，峭度，峰值指标，阈值裕值指标，峭度指标等，然后用RBF做聚类(The method of feature extraction in time domain includes mean value, root mean square value, skewness, kurtosis, peak value index, threshold margin index, kurtosis index, etc. Then RBF is used for clustering.) Platform: |
Size: 1024 |
Author:TWO |
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Search - Root Mean Square in matlab