Description: Linear-Predictive-Coder
MATLAB Implementation of LPC algorithm for speech signal
# Why LPC?
In communication systems it is often necessary to transmit audio(speech) signal in compressed or encoded form because of bandwidth limitation of the channel. In this regard, ‘Linear predictive coding(LPC)’ is an effctive method of speech coding at a low bit-rate.
# Features
** Analysis/Encoding phase,Synthesis/Decoding phase.
**Human voice modelled with all-pole filter.
** LPC parameters(filter coefficients, pitch, gain etc) extraction at the decoding phase.
** Non-overlapping frames of 30 milliseconds in duration
# How To Run
** Make sure MATLAB(latest version) is installed
** Put both files(LPC.m with .mp3 file) in the same folder
** Open LPC.m file and run it.
## Comments
Different audio (.mp3) files can be coded/decoded by changing the input file name in the code. Platform: |
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The main aim of our project is to simulate CDMA modem using DS-SS (Direct sequence spread spectrum) in MATLAB. Spread spectrum is basically type of modulation that spreads data transmission across available frequency band, in excess of minimum bandwidth available. We will be generating code by multiplying with pseudo random code in order to generate spread spectrum, transmitting it over a common frequency band and de-spreading the signal using same pseudo random code at the receiver. Also our aim is to simulate the de-spreading of the received CDMA signal in the presence of AWGN .
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Description: 用matlab仿真实现了25 kHz 带宽内同时传送总共48 kbits 的两路语音-Matlab simulation realized within 25 kHz bandwidth send a total of 48 kbits two way voice at the same time Platform: |
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Description: 用matlab仿真实现了25 kHz 带宽内同时传送总共48 kbits 的两路语音-Matlab simulation realized within 25 kHz bandwidth send a total of 48 kbits two way voice at the same time Platform: |
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Description: 用matlab仿真实现了25 kHz 带宽内同时传送总共48 kbits 的两路语音(Matlab simulation realized within 25 kHz bandwidth send a total of 48 kbits two way voice at the same time) Platform: |
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Description: LWP是一种Matlab / Octave工具箱实现局部加权多项式回归（也被称为局部回归/局部加权散点平滑/黄土/ LOWESS和核平滑）。使用此工具箱，您可以使用九个具有度量窗口宽度或最近邻窗口宽度的任意一个内核来拟合任意维度的数据的局部多项式。还提供了一个优化内核带宽的函数。(LWP is a Matlab/Octave toolbox implementing Locally Weighted Polynomial regression (also known as Local Regression / Locally Weighted Scatterplot Smoothing / LOESS / LOWESS and Kernel Smoothing). With this toolbox you can fit local polynomials of any degree using one of the nine kernels with metric window widths or nearest neighbor window widths to data of any dimensionality. A function for optimization of the kernel bandwidth is also available.) Platform: |
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