codebuilder_i605mc

1、分别生成两种信号（正弦波、方波、三角波、锯齿波、Sinc波形等）+噪声（高斯随机噪声、均匀噪声） 要求：频率：学号*100； 幅度：学号/10 相位：学号*pi/180 点数：学号*64 2、同时在一个图形中进行显示： 要求：标注X轴、Y轴、题目、颜色、样式、线型标注等。 3、进行信号分析及结果显示（对结果也要图形标注，同2） 要求：相关分析 卷积运算 求和运算 频谱分析（最大值、测频） 4、对上述原信号及信号分析结果分别存成EXCEL文件、文本文件和二进制文件，命名为名字+班级+学号+后缀(1, respectively, to generate two signals (sine wave, square wave, triangle wave, sawtooth wave, Sinc waveform, etc.)+ noise (Gaussian random noise, uniform noise) requirements: Frequency: No.* 100 margin: Student ID/10 phase: learning* pi/180 Points: No.* 642, in a graphical display: Requirements: X-axis label, Y axis, the title, color, style, linear marked. 3, signal analysis and results display (graphical results also marked with 2) requirements: analysis convolution summation spectrum analysis (maximum frequency measurement) 4, the original signal and the signal analysis results were kept into EXCEL files, text files and binary files, named for Name the+ class++ suffix number)

适合大家的学习滑模变算法，刘金琨老师书上的例子。(Sliding Mode algorithm suitable for all learning, Liu Jinkun teacher book example.)

这是一个SSB移相法分析信号的Systemview源代码。(This is a SSB phase shift analysis of the signal source code Systemview.)

仿真未编码和进行（7,4）汉明码编码的QPSK调制通过AWGN信道后的误比特率(Simulation is not encoded by AWGN channel bit error rate and the (7,4) Hamming code coded QPSK modulation)

实现香农编码，计算平均码长、平均信息熵和编码效率。(Shannon coding, and calculate the average code length, the average information entropy coding efficiency.)

经验模态分解（Empirical Mode Decomposition,EMD）法是美国国家宇航局美籍华人黄锷（N. E. Huang）等人于1998年创造性地提出的一种新型自适应信号时频处理方法，特别适用于非线性非平稳信号的分析处理。(Empirical Mode Decomposition (Empirical Mode Decomposition, EMD) method is a new kind of video processing method adaptive signal NASA Chinese-American yellow E (NE Huang), who in 1998 proposed a creative way, especially for non- Linear analysis and processing non-stationary signals.)

16psk通信系统的信噪比与误码率计算并绘图(16psk communication system signal to noise ratio and bit error rate calculation and mapping)

学习并找到降噪方法，对语音信号背景噪声做处理，使得声音更清晰。(The background noise is the most common factor degrading the quality and intelligibility of speech in recordings. Spectral subtraction can lower the noise level without affecting the speech signal quality. In this paper, we have studied and implemented to reduce the background noise of the voice signal, and to make improvements to reduce the background noise of the experiment. Not only with the spectral subtraction of the noisy signal of the transformation, we improve the traditional spectral subtraction based on the introduction of the parameters, by adjusting the parameters(α、β、γ) to achieve better enhancement.)

software engineering C#

《MATLAB时尚百例实例》实例14-27()