Questions tagged [linear-prediction]
The linear-prediction tag has no usage guidance.
43
questions
0
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0answers
9 views
audio quality evaluation of Linear prediction resynthesized signal
Does anybody try the audio quality of linear prediction resynthesized signal using a music file? Using the frame length of 50 or 20 ms. And have you ever tried the objective evaluation using the ...
0
votes
1answer
24 views
Linear prediction and filter stability
I am currently trying to implement an iterative block-wise algorithm in which AR coefficients are computed for each block.
There is a issue with my code where values get too large, and I was ...
0
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0answers
92 views
How to find Coefficients of Autoregressive (AR) model using least means square (LMS) Algorithm without having future signal?
I want to do two things.
Estimating Coefficients of AR model using LMS
Using Coefficients found in step 1 and predict future samples of a signal using AR equation.
I don't have a desired signal so I ...
0
votes
0answers
15 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
134 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
44 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
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0answers
45 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
30 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
34 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
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0answers
541 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
88 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
187 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
324 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
81 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
225 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
1k 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 ...
3
votes
0answers
186 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
497 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
455 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
287 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
53 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 = \...
3
votes
4answers
741 views
Compression algorithms specific to complex signals
I am looking for (lossy or lossless) compression algorithms dedicated to complex signals. The latter could be composite data (like the left and right for stereo audio), a Fourier transformation or an ...
0
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0answers
264 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
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1answer
1k 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
6k 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 ...
4
votes
1answer
533 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
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0answers
98 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
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0answers
88 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
215 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
47 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 ...
2
votes
1answer
282 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
666 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
217 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
362 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
209 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
121 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
136 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
1k 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
948 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
115 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
325 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 ...
7
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?
...
