Stack Exchange Network

Stack Exchange network consists of 175 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange

Questions tagged [linear-prediction]

The tag has no usage guidance.

0
votes
0answers
8 views

Pole location in linear prediction of sinusoidal signal

As mentioned in texts [Ref: Vaidyanathan P.P, The Theory of Linear Prediction], that a process which is perfectly an AR(p) process, or a sinusoidal process, can be perfectly reconstructed through ...
1
vote
1answer
75 views

Can Temperature data be predicted using adaptive filter using LMS algorithm?

I am working on a project which requires me to implement adaptive filter as a predictor. I have just started on adaptive filter and I intend to use least mean square algorithm for weight adjustment. ...
0
votes
1answer
32 views

AR Modeling: Why residual is white noise?

I was going through AR modeling. The AR model of a covariance stationary process can be expressed as: $$x[n]=\sum\limits_{i=1}^{p} \alpha_i x[n-i] + \epsilon[n]$$ where $p$ is the model order and $...
0
votes
0answers
28 views

Find optimal coefficients of linear predictor [duplicate]

I have the following question I realised it's a two step forward linear predictor, so I assumed the order has to be M=2. Now, I'm actually trying to find optimal coefficients but I'm struggling to ...
0
votes
1answer
17 views

Adaptive Predictive Coding: Transmit signal AND prediction coefficients

I'm not well versed in the literature so please forgive/inform me if my terminology is wrong: I have a bounded real-valued, discrete-time signal $x_n \in \mathbb [0, 1]$, and I want to (lossily) ...
0
votes
1answer
33 views

Practical insightful time domain functions [closed]

This question might be a little bit different, but i am having hard time to find some sort of a list/book/website/advice, with very practical time domain functions that provides useful insgihts for a ...
1
vote
0answers
128 views

Linear Predictive Coding example in MATLAB

I have some data that is highly correlated and I wanted to see if I could try and encode it using linear predictive coding (LPC). Here is how I've been understanding the process: Encoding Generate ...
1
vote
0answers
41 views

Understanding linear predictive coding in MATLAB

I want to test my understanding of linear prediction by running it on some test data in MATLAB. The way I understand it is if I have some data that is correlated, I can encode the signal with linear ...
2
votes
1answer
88 views

Linear Predictive Coding for general signals

I have a signal that's monotonic and roughly linear and have been looking at using Linear Predictive Coding to encode information and compress my signal. I guess my first general question is if this ...
4
votes
3answers
272 views

Is Linear Prediction ever exact?

I'm just learning about linear prediction and was wondering whether or not there are any signals that would produce no error if run through a linear prediction algorithm. I was thinking (maybe naively)...
1
vote
2answers
60 views

Image Interpolation Using the Yule Walker Equations

I have been studying about the Yule-Walker equations for prediction of a time series data from knowledge of past values of the series. Is there any way I can use the same in an image to exploit the ...
2
votes
1answer
203 views

Autoregressive modeling (linear prediction) of electrical transmission lines?

I've read that the reflection coefficients in speech processing (as computed by the Levinson-Durbin algorithm for solving the Yule-Walker equations) "represent the fraction of energy reflected back" ...
3
votes
0answers
638 views

Pre-emphasizing in speech recognition

Usually, in speech recognition, the techniques that are used are based on the linear prediction model (Fant, 1960). Parallel to this, the human speech production mechanism causes energy to drop ...
2
votes
0answers
125 views

Intuitions on Kumaresan-Tufts algorithm for exponential fit

I am analyzing a transient signal presumably consisting of superposed exponentials. Such a case is indicated for the Prony analysis, but my data aren't noiseless enough, so I have turned to the ...
1
vote
1answer
364 views

How do I go from LPC coefficients to a filter polynomial?

I've recently begun experimenting with LPC, and while I understand that it works, I'm still slightly lost on why it works. Specifically, I understand that LPC involves finding coefficients $a_1, a_2, ...
2
votes
1answer
295 views

Predicting account balance based on historical data

Given the values of a bank account balance over time (see figure below as an example), how can one predict the account balance at a given date in the future ? Should I just fit one linear regression ...
2
votes
0answers
236 views

How to use linear predictive coding to compress voice diphone samples?

I'm working on an experimental diphone / unit selection speech synthesizer for my native language which lacks good speech synthesizer for blind people. The problem is that recorded unit library can ...
1
vote
0answers
51 views

Variance and Co-variance of a Linear Forecast

Consider a linear forecasting problem where all shocks $\{\epsilon_i\}_1^n$ are independently distributed with $\epsilon_i\sim N(0,\sigma_i^2)$ for all $i$. Suppose you want to forecast $\theta = \...
0
votes
0answers
243 views

Prediction-error filter for images

I am interested in studying local pixel value dependencies in images and I am wondering if it exists a general form of prediction-error convolutional filter that is able to suppress the image's ...
0
votes
1answer
808 views

Linear prediction (LPC) of Sine wave samples around maximas

I think I missed class when this was explained ... Anyway as part of a bigger project I have to implement a LPC to predict 2-3 future values of a sinusoidal process. I wrote a small Matlab m-file to ...
3
votes
3answers
5k views

What is the need for prediction filter in PCM and DPCM?

The DPCM works by the difference between actual samples and predicted samples. If we already have the actual samples, we can quantize it and encode it later. But why we use prediction filter? And ...
5
votes
1answer
392 views

How is cross-correlation related with orthogonality?

In linear prediction we can say that in case of optimum linear predictor the error with be orthogonal to data. And when we derive minimum mean square error for $\underline{y} = \mathbf{a}\underline{x} ...
0
votes
0answers
89 views

Sample-By-Sample Linear Prediction

As I understand it and have it currently implemented, linear prediction [via Burg's method or the autocorrelation method] is a block algorithm. Hence, there will be latency involved because one must ...
1
vote
0answers
78 views

Noise Robust Linear Prediction

So it appears that Linear Prediction as performed via Durbin Recursion is sensitive to additive noise. What are some techniques for linear prediction that may be more robust? Can anyone supply a link ...
-1
votes
1answer
206 views

100 samples ahead signal prediction [duplicate]

I have a signal sampled at 100 sample per second. After low pass filtering of 200 order and some calculation such as zero crossing detection, I am getting around 1 second delayed signal. I want it in ...
1
vote
0answers
46 views

Turn a decision problem into a linear filter problem

Let $x[n]$ be a time-series, and two filters: $A[n] = a_0 x[n] + a_1 x[n-1] + ... a_q x[n-q]$ $B[n] = b_0 x[n] + b_1 x[n-1] + ... b_r x[n-r]$ I think the answer is No, but is there a way to have ...
3
votes
1answer
241 views

Linear Prediction of AR Process

A discrete signal x is generated by the recursive process $$ x_n = x_{n-1} - 0.2 x_{n-2} + w_n $$ where $w_n$ is white noise with zero mean and unit variance. What is the optimum order of a linear ...
1
vote
1answer
575 views

Division by zero in Levinson–Durbin recursion?

I am doing a LPC analysis of a speech signal using the autocorrelation method. To calculate the LPCs I am using the Levinson–Durbin recursion. In my literature the error is initialized with the first ...
2
votes
0answers
191 views

Spectral Whitening: Approches

Given the absence of information about the algorithms of spectral whitening functions in software packages: How many ways do you know for doing spectral whitening? What are the differences?
0
votes
2answers
309 views

pitch extraction for speech

I am building an LPC analysis tool, and am at the point of needing to do pitch period analysis. I was initially interested in using the Gold & Rabiner algorithm for this, and got a hold of a ...
-1
votes
2answers
200 views

Linear Predictive Coding and Block Size

I'm experimenting with linear predictive coding as a low-complexity audio compression method, and I'm observing something very odd. I'm compressing a 20 MB mono 16-bit PCM song in different block ...
0
votes
2answers
108 views

Is there any relationship between the FFT and linear prediction?

Is there any relationship between the FFT and linear predictive methods? Can an FFT result or the input to an FFT be modified to do non-circular prediction/extrapolation from the FFT results.
0
votes
0answers
133 views

Adaptive calculations of Wiener filter coefficients

Suppose,I have an input of length of lenght 100. data=[x0...x99]; I take a window of lenght 11 from x0 to x10. windowed data=[x0 x1 x2 x3 x4 x5 x6 x7 x8 x9 x10], now, I compute 7 wiener coefficients ...
1
vote
1answer
916 views

Adaptive Wiener Filter Coefficients Calculation

I want to extrapolate a signal X of length 11, using the weiner filter coefficients W of length 7. The procedure I am using is as follows: Compute the autocorrelation matrix upto lag 8 . Using ...
0
votes
1answer
893 views

Derivation of Yule-Walker Equation for LPC

I have derived the Yule-Walker equation as shown below. \begin{align} \hat s(n) &= -\sum_{k=1} ^ p a_k s(n-k)\\ e(n) &= s(n) - \hat s(n) = s(n) + \sum_{k=1}^pa_k s(n-k) \end{align} In order ...
2
votes
0answers
111 views

Voice sample prediction scheme

I have some telephone voice audio with occasional "blips" in the audio. The blips appear to come from an IP link buried in the PSTN (this is a conceptual explanation, so don't worry about things like ...
3
votes
2answers
297 views

Linear predictive model convolution

Accidentally asked this question in the general area and was told to ask here, so... I've been trying to develop a lightweight, relatively-fast-to-decode sound compression format for use in my gaming ...
6
votes
1answer
3k views

Speech Compression - In LPC how does the linear predictive filter work on a general level?

Hi I'm taking a multimedia systems course and I'm preparing for my exam on tuesday. I'm trying to get my head around LPC compression on a general level, but I'm having trouble with what is going on ...
9
votes
1answer
1k views

Theory behind Linear Predictive Coding (LPC)

What is the theory behind LPC? Why are(were) certain implementations of LPC said to be more tolerant of transmission or encoding errors quantization than other compressed voice encoding schemes? ...