# Questions tagged [estimation]

In signal processing, estimation is a technique for approximating an unobserved signal from an observed signal containing noise.

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### SNR estimation: signal with unknown amplitude and Gaussian noise

I would like to know can anyone suggest me techniques to estimate the SNR for a given noisy signal. I do not know the amplitude of my signal but I do know that noise is Gaussian. I have tried to do ...
601 views

### What is the computational complexity of Spectrum Estimation Algorthms and What they depend upon?

There are lots of spectrum estimation techniques, each with some pros and cons. Algorithms like: Music Welch's method Yule-Walker AR method Periodogram modified covariance method multitaper method (...
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### Help in problem formulation for estimation of image as a feature vector - SISO or MIMO FIR channel model?

Based on the paper Blind Image deconvolution: A feature vector is a list of numbers used to represent an image. The feature vector for my case takes values as symbols $-1,1$. An instance or an ...
866 views

### What are the advantages of higher order Kalman Filters like EKF, UKF?

Kalman Filter provides the optimal estimate of the states of a stochastic dynamical system if the system is linear, the measurements are also linear functions of states and the errors in system ...
157 views

### Different results for different orders of estimating AR model using Yule-Walker equations

I'm trying to use MATLAB to estimate the AR parameters to the following filter: $$H(z) = \frac{1}{1-0.5z^{-1}+0.25z^{-2} -0.25z^{-4}}$$ As I can see, the process at the output of this filter depends ...
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### Estimate/Compute parameters of image dataset

I have a dataset of images taken by Kinect (RGB and D) How can I extract the following information only from the images: Frame rate Camera height The dataset containes images of person (s) moving ...
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### Any estimation algorithms that allow a user to indicate that certain Solutions are impossible?

Variations of the Kalman filter and other algorithms are used for navigation and target tracking. Often times certain solutions might as well be deemed impossible based on known topography in the area....
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### Goodness of fit for complex valued curves (i.e. frequency responses in frequency domain)

My apologies for perhaps the stupidity of this question. Presume that one has the 'frequency response' $Y_{data}(k)$ of a system and also has an estimated model $Y_{syn}(k)$ that fits the data. How ...
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### Good Reference Problem to Test Filtering/Estimation Algorithms

I am looking to figure out if a current filter algorithm I have built could be useful for some problems I am looking into at work. It isn't a Kalman filter, but is instead making estimations using a ...
125 views

### Estimation of accelerating target using position measurements only

I am currently thinking about approaches to estimating the position and velocity of an accelerating target. At this time, I have tried a few approaches that work alright. I have tried two variations ...
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### Methods of combing two parameter estimates

If you have two different methods of calculating a continuous parameter (eg. heart rate), each with their own uncertainty, what would be some common methods of combining these parameters to create a ...
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### 1/f noise parameter characterization

I would like to characterize 1/f noise in some time series data. I would like to estimate the 1/f noise corner, and the standard deviation of the 1/f noise component and white noise component. The ...
146 views

### Problem using MMSE estimation of channel frequency response

I need to model the minimum mean square error (MMSE) performance in estimating channel frequency response. I have channel's power delay profile (PDP) as a table with tap delays and powers. The ...
160 views

### RLS Algorithm Convergence

I am looking for some help to understand the concept how RLS converges? If possible to present it graphically that would be best. It is very easy to understand the understanding of convergence in case ...
300 views

### Cost function for adaptive algorithms

I am having little difficulty to understand that why most of the adaptive algorithms use error power or addition of error power as cost function/minimization criterion. I have read that minimization ...
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### Estimate camera generalized velocity from consecutive frames

Let's suppose I have a camera which can move freely in 3D space and has 6 degrees of freedom. Is it possible to estimate the linear and angular velocity of the camera from 2 or more consecutive frames?...
644 views

### Cross-Correlation Signal Delay Estimation Variance

I am working on a project which intends to use Time Difference of Arrival (TDoA) for localization. Firstly, my understanding is that a matched filter is the most common method for estimating signal-...
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### Looking for the Concept About All In One Curve Fitting

I know that there are some Technic for finding curve fitting like polyfit() or pinv(). so we can get a some polynomial equation. it's OK good. I can get successively a polynomial equation for each ...
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### Confusion related to PN sequence : Terminology and application in statistical signal processing

A Pseudo-random Noise (PN) sequence is a sequence of binary numbers, e.g. ±1, which appears to be random; but is in fact perfectly deterministic. The sequence appears to be random in the sense that ...
620 views

### Subsample Time Delay Estimation

Often we need to estimate the time difference of arrival between two signals to find the location of a target. Many algorithms gives the time delay corresponding to a sample number or time delay is a ...
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### What is the estimator used in this paper for system identification?

The paper System Identification using Symbolic Chaotic Sequence proposes EM-UKS estimator for system identification of a linear FIR channel when excited by non linear input. In Fig 3 of the paper ...
188 views

### Expectation maximization of moving average with binary source input

I am trying to do blind system identification of a univariate linear FIR model: I am unsure if the approach is correct or not and any help to further proceed with the maximization will be great. ...
For sequences that are transmitted over channels with memory $\mu=n$ and response H=$[h_0 h_1 \ldots h_n]$,Viterbi algorithm implements Maximum Likelihood (ML) detection and BCJR implements Maximum A-...