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GraphicSpectrumAnalysis
- 使用VC++实现,对图形做频谱分析.文档中含有相关知识背景说明及实际测试结果.-use of graphics power spectral analysis. Documents containing background notes related knowledge and practical test results.
code_duan
- 实现差分编码和数字分相码的波形以及功率谱密度的仿真，取样点数默认为2^14。-achieve Differential encoding and digital Phase code and the waveform of the power spectral density of simulation, The default sampling points for 14 ^ 2.
amii
- 实现常用线路码型AMI（RZ）码的波形和功率谱密度的仿真。-achieve common line code-AMI (RZ) code and the waveform of the power spectral density of simulation.
ARMA_LAST
- This function provides an ARMA spectral estimate which is maximum entropy satisfying correlation constraint (number of poles)and cepstrum constrains (number of ceros) The function requires 3 inputs: Input signal, Order of denonominator, Order
AWGN RAY
- 基于MATLAB的QPSK仿真（AWGN高斯信道和瑞利信道），包括系统框图、功率谱密度、星座图。另外还有一个当发生100个错误时的误码率，高斯信道和瑞利信道下仿真的误码率和误比特率与理论值对比。-MATLAB-based simulation of QPSK (AWGN Gaussian channel and Rayleigh channel), including system block diagram, the power spectral density, constellation
xunhuanpuguji
- 基于matlab实现的循环谱估计算法，可以对具有循环平稳特点的信号进行参数估计-Matlab-based spectral estimation algorithm to achieve the cycle, you can have the characteristics of the signal cyclostationary parameter estimation
MSK
- MSK FSK的调制程序及其功率谱密度函数图像-MSK FSK modulation process and its power spectral density function of image
基于fft的频谱分析
- 基于fft的频谱分析程序。硬件由dsp实现，数据通过串口送至计算机进行频谱分析显示。 附两篇文档！-based on the spectral analysis procedures. Hardware Implementation by dsp, data sent to the computer through the serial spectrum analysis shows. A two documents!
BPSK
- BPSK循环谱matlab仿真程序，可用于OFDM系统干扰循环谱分析。-BPSK cycle simulation program matlab spectrum, OFDM systems can be used to interfere with the cycle spectral analysis.
er
- 用VB语言实现随机信号的功率谱密度算法和自相关函数。-VB language with random signal power spectral density and autocorrelation function algorithm.
Untitled1
- 周期图方法频率估计 傅里叶变换求功率谱密度 用Matlab编程仿真实现-Periodogram method of frequency estimation Fourier transform for power spectral density using Matlab programming simulation
spectral-subtraction-algorithm
- 本文首先研究了语音激活检测算法。对基于短时能量和短时过零率双门限法语音激活检测的噪声估计算法做了研究及仿真，同时还研究了一种基于最小子带能量的噪声估计方法。-Firstly, studied voice activity detection algorithms. Based on activity detection and short-term energy zero rate threshold method voice noise estimation algorithm to do t
FAM
- 用于计算谱相关函数的时域平花FFT积累算法，可改参数，改输入信号类型-calculate spectral correlation function by using time smoothing FFT Accumulation Algorithm, you can change the parameters, and the type of input signal
Matlab_code_CCS-MMV
- 基于原子范降噪的线谱估计技术，内容主要高分的压缩感知线谱估计，在雷达领域有着非常广泛的用途。-Atomic norm denoising with applications to line spectral estimation for radar, sonar and wireless commmunication
PSD
- 功率谱密度，主要求 功放预失真补偿前后的功率谱密度-Power spectral density, mainly for power amplifier predistortion compensation before and after the power spectral density
pa_in_out_memoryless
- 预失真补偿后的图形,采用快速傅里叶变换（Fast Fourier Transform, FFT） 计算得信号的频率数据，再利用得到的频率数据计算功放预失真补偿前后功率谱密度 样值-Predistortion compensation of graphics, using the Fast Fourier Transform, Fast Fourier Transform and FFT) Calculate signal frequency data, then get the fr
bon-cour-QPSK
- Phase shift keying (PSK) is a large class of digital modulation schemes. PSK is widely used in the communication industry. In this chapter we study each PSK modulation scheme in a single section where signal descr iption, power spectral density,
SOLC_A
- Phase shift keying (PSK) is a large class of digital modulation schemes. PSK is widely used in the communication industry. In this chapter we study each PSK modulation scheme in a single section where signal descr iption, power spectral density,
PSO_solc_SansComponsa
- Phase shift keying (PSK) is a large class of digital modulation schemes. PSK is widely used in the communication industry. In this chapter we study each PSK modulation scheme in a single section where signal descr iption, power spectral density,
TCPxiaobo
- 用DCT变换和小波变换对全色光学图像和多光谱图像进行融合，生成同一图像。-Use DCT transform and wavelet transform of the panchromatic optical images and multi-spectral image fusion to generate the same image.