Description: 实现对数压缩PCM和线性PCM的信噪比特性曲线的仿真，非均匀量化级数为n=8和n=6。-realization of a number of PCM compressed and linear PCM signal-to-noise ratio of the characteristic curve simulation, non-uniform quantization Series n = 8 and n = 6. Platform: |
Size: 915 |
Author:段美姣 |
Hits:
Description: purpose
simulates embedding and detection of watermark in random noise using QIM (quantization index modulation), uses non-linear scaling
compile
gcc -g -o nlqim nlqim.c -lm
-purpose simulates embedding and detectio n of watermark in random noise using QIM (quanti index modulation. 5), uses non-linear scaling compile gcc-g-o nlqim nlqim.c - lm Platform: |
Size: 1019 |
Author:王国树 |
Hits:
Description: 实现对数压缩PCM和线性PCM的信噪比特性曲线的仿真，非均匀量化级数为n=8和n=6。-realization of a number of PCM compressed and linear PCM signal-to-noise ratio of the characteristic curve simulation, non-uniform quantization Series n = 8 and n = 6. Platform: |
Size: 1024 |
Author:段美姣 |
Hits:
Description: purpose
simulates embedding and detection of watermark in random noise using QIM (quantization index modulation), uses non-linear scaling
compile
gcc -g -o nlqim nlqim.c -lm
-purpose simulates embedding and detectio n of watermark in random noise using QIM (quanti index modulation. 5), uses non-linear scaling compile gcc-g-o nlqim nlqim.c- lm Platform: |
Size: 1024 |
Author:王国树 |
Hits:
Description: 线性量化。读取WAV文件，用不同的比特数量化，抽样频率在8khz-Linear quantization. Read WAV files, with different number of bits, the sampling frequency of 8kHz Platform: |
Size: 1024 |
Author:kenny |
Hits:
Description: 直接数字频率合成器中相位累加杂散，幅度量化杂散及DAC非线性杂散的功率谱密度曲线频谱图-Direct digital frequency synthesizer spurious accumulation phase, amplitude quantization spurious and non-linear DAC spurious power spectral density curve of the spectrum graph Platform: |
Size: 1024 |
Author:王莹莹 |
Hits:
Description: PCM的A律U律实现代码：16位线性量化的数据转换成8位非线性的PCM数据（13折线法）-U of A law PCM realize Legal Code: 16-bit linear quantization of the data into eight non-linear PCM data (13 line method) Platform: |
Size: 2048 |
Author:黄翠翠 |
Hits:
Description: 线性二次最优控制加权阵遗传算法优化适应度函数m文件；模糊控制器量化比例因子遗传算法优化适应度函数m文件-Linear quadratic optimal control weighted array genetic algorithm fitness function m documents quantization scale factor of fuzzy controller optimized by GA fitness function m file Platform: |
Size: 4096 |
Author:张立迎 |
Hits:
Description: ：用C 语言实现了一个用于控制家电开关的声音模块. 该声音模块采用当前语音识别系统的主流技
术——隐马尔可夫模型（HMM）技术，以及线性预测倒谱计算和矢量量化技术. 命令（单词）的正确识别率
在97 以上. 介绍了声音模块的设计方案，并就实现该声音模块的过程中所遇到的具体问题进行了讨论.-: The C language realization of a switch used to control the voice module appliances. The sound module voice recognition systems using current mainstream technologies- Hidden Markov Model (HMM) technology, as well as the linear prediction cepstrum calculation and vector quantization technology. command (word) the correct recognition rate in more than 97 . introduced a sound module design and the realization of the sound module on the course of the specific problems encountered were discussed. Platform: |
Size: 200704 |
Author:刘文 |
Hits:
Description: 正弦波信号的均匀量化和线性编码
A/D 变换，实数的线性编码
D/A 变换，实数的线形译码-Uniform quantization of sinusoidal signal and linear coding A/D conversion, the linear coding real D/A conversion, real decoding of linear Platform: |
Size: 1024 |
Author:zhangwei |
Hits:
Description: Simulation of Residual Excited Linear Prediction (RELP) coding for speech:
This simulation give your voice or available clear wav file.This encoder have linear predictor that decreases signal s dynamic (lower quantization level). This technique also use lowpass filtering to make lower bandwidth and reconstruct it with three methods that is chosen in decoder. For example duplicate same spectrum of encoded signal that filtered in upper frequency.-Simulation of Residual Excited Linear Prediction (RELP) coding for speech:
This simulation give your voice or available clear wav file.This encoder have linear predictor that decreases signal s dynamic (lower quantization level). This technique also use lowpass filtering to make lower bandwidth and reconstruct it with three methods that is chosen in decoder. For example duplicate same spectrum of encoded signal that filtered in upper frequency. Platform: |
Size: 855040 |
Author:Ardalan |
Hits:
Description: 用S函数编写的量化器
量化步长为非线性
即 量化步长可调
-Prepared by S function to quantify the quantizer step size for the non-linear quantization step size that is adjustable Platform: |
Size: 5120 |
Author:天行健 |
Hits:
Description: 基于MATLAB实现图像线性量化的源码，通过输入量化参数实现不同等级量化-Based on MATLAB to achieve linear quantitative image source, by entering the quantization parameters to achieve different levels of quantization Platform: |
Size: 1024 |
Author:wshrf |
Hits:
Description: VQ声纹识别算法和实验.
摘要：采用线性预测倒谱系数(1inear prediction cepstrum coefficient，LPCC)作为语音的特征参数，矢量量化(vector quantity，VQ)方法进行模式匹配，探讨声纹识别以实现身份认证，并对此识别方法进行了相关的实验．通过验证，这种方法可以区分不同的说话人，并且在做说话人辨认实验时可达到较高的识别率．-VQ pattern recognition algorithms and experimental sound. Abstract: The linear prediction cepstral coefficients (1inear prediction cepstrum coefficient, LPCC) as the voice of the characteristic parameters, vector quantization (vector quantity, VQ) method of pattern matching, pattern recognition of sound in order to achieve authentication and identification methods relevant to this experiment. Validated, this method can distinguish between different speaker, and speaker identification experiments to do to reach a higher recognition rate. Platform: |
Size: 171008 |
Author:海边贝壳 |
Hits:
Description: For a file(.wave)
• Find the sampling frequency and the number of bits per sample.
• Re-quantize the samples using the following methods:
o Linear Quantization
o A-Law Companding with A=87.6
o μ-Law Companding with μ=255
• Use a mid-rise quantizer with 4, 5, 6, 7, and 8 bits per sample.
• Obtain the signal-to-quantization noise ratio (SQNR) for each of the
above 15 cases.
• It is required to plot the SQNR (dB) versus the number of bits per
sample for linear quantization, A-law companding, and μ-law
companding. All 3 plots may be on the same figure, if convenient.
-For a file(.wave)
• Find the sampling frequency and the number of bits per sample.
• Re-quantize the samples using the following methods:
o Linear Quantization
o A-Law Companding with A=87.6
o μ-Law Companding with μ=255
• Use a mid-rise quantizer with 4, 5, 6, 7, and 8 bits per sample.
• Obtain the signal-to-quantization noise ratio (SQNR) for each of the
above 15 cases.
• It is required to plot the SQNR (dB) versus the number of bits per
sample for linear quantization, A-law companding, and μ-law
companding. All 3 plots may be on the same figure, if convenient.
Platform: |
Size: 1024 |
Author:mshmsha |
Hits:
Description: 线性离散码量化处理及实现研究，对线性离散码进行量化处理，对整个过程的实现做了很大程度的改进-Linear discrete code the quantization process and realization of linear discrete code carries on the quantification treatment, the whole process of the realization of the do a large degree of improvement
Platform: |
Size: 2126848 |
Author:zhouxiaolin |
Hits:
Search - linear quantization