Signal Processing Stack Exchange
Signal Processing Stack Exchange

Questions tagged [parameter-estimation]

65 questions
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Simple and Effective Method to Estimate the Frequency of a Single Sine Signal in White Noise

Given a sinusoidal signal, how can we efficiently determine its frequency?
RyanRonald
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Fast pitch recognition

I need to detect pitch (measure signal frequency) while the musicians play music, giving a warning if they are out of tune, but music happens to be a bit too fast for FFT (Fast Fourier Transform). Below I try to give a technical description of the…
18446744073709551615
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MMSE Estimation - Fusion of 2 Measurements

Let's say I have 2 measurements of the same phenomenon (for example current temperature) and I want to find the MMSE (minimum mean square error) estimator, i.e to minimize the MSE (mean square error). The measurements are independent and the noise…
Nir
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Sequential Form of the Least Squares Estimator for Linear Least Squares Model

I'm currently working on a project in which I need to find the tilt of a surface. Let's assume I'm only concerned with a single dimension tilt (i.e. slope) to begin. I currently have the ability to calculate parameters of Affine Functions as…
Izzo
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Concept About Estimated Standard Deviation

I am looking for the concept about how to estimate standard deviation. Actually I'm not sure how can I get a concept the estimate standard deviation ? If you know the concept, then would you let me know it here? Also if you have any reference or…
gmotree
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Is the Wiener filter operating at the Cramér–Rao bound?

I have been told (Wikipedia agrees) that the Wiener filter is optimal when signal and (additive) noise are WSS. Optimal in the sense that it minimizes the mean-square error. The Cramér–Rao bound is the lower bound on the variance of an unbiased…
fabian_pedd
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Determine the Signal Curve from Parameters of a Power Curve by Noisy Measurement

I have a class of signals described by function: $$ f(inc,d,t)=inc\cdot t^d $$ where inc and d have a finite set of values like 1, 2, 3, i.e. $$ inc, d\in \left \{1,2,3 \right \} $$ and $$ 0\leq t<1 $$ Example plots: I need to determine parameters…
PSz
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How to Linearly Combine Two Unbiased Estimators of One Parameter without Knowledge of Their CoVariance?

I have two unbiased estimators of one parameter, $\tau$. The first estimator, $r_1$, is the better estimator with lower variance than the second estimator, $r_2$. I also have: $ \mathbb{E} \left[ {r}_{1} \right] = 0.8 \tau $ , and $ \mathbb{E}…
Elnaz
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Maximum Likelihood Estimator (MLE), MMSE and LS - Are All of Them Regressor, Estimator and Predictor?

Can all three criteria ML, MMSE, and LS be called regressor, estimator, and predictor ? If not, an intuitive explanation of why they can't be, would be good.
mohammadsdtmnd
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Maximum Likelihood for Colored Noise

I have the following question about the maximum likelihood (ML) in presence of inter-symbol interference and colored noise. Assume the communication system is as follows. Information source, modulator, transmit pulse filtering, channel, AWGN,…
Noor
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Understanding the Difference Between MAP Estimation and ML Estimation

There are a number of possible criteria to use in making decisions. Can someone elaborate on the difference between ML and MAP for a sequence of BPSK symbols impaired by Gaussian noise ?
Abby_DSP
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Damped spring mass system - parameter estimation

I've tried to calculate the parameters of a damped spring mass system of the form $m~ y''(t)+d~y'(t)+c~y(t)=F(t)$ but I have some problems determining the mass m of the system. The damped spring mass system is given by a MATLAB function …
Phobos
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Estimate Variance of Additive White Gaussian Noise (AWGN) Given Multiple Realizations with Different Mean

Given $ N $ images of the same scene, where each image is corrupted by additive white Gaussian noise of the same variance $ {\sigma}^{2} $. How can $ {\sigma}^{2} $ be estimated? So we have an Image $ X \in \mathbb{R}^{m \times n} $ which we have…
zacmar
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Dominant Frequency Peak Decreases with Increasing Window Size

I have a signal that looks like this. I analyse it using fast Fourier transforms to identify the frequency with the largest peak, which is always close to zero. (There are no other clear peaks.) If I use windows of different sizes (by "window" I…
Lyngbakr
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Why Is The Maximum Likelihood Estimation (MLE) Method Taken as the Benchmark for Comparing with Other Methods?

In many research articles the performance of an estimation method is compared to that of the ML estimation performance. If the performance of the method does not achieve the ML estimation performance, then the method is 'suboptimal' or not good…
Srishti M
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