Questions tagged [least-squares]

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Doubt regarding scaling of Welch Overlap Segment Averaging with Lomb Scargle

I am doing something similar to this question Comparison of results own implementation and python signal.welch. In my case there is no Welch method associated with the scipy lomb scargle spectrum so I ...
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3 votes
2 answers
114 views

Constrained Least Squares Filter Design

I would like to design a complex FIR filter, $h$, for a known signal that produces a desired output: $d$ = $s*h$ (where $s$ is my signal and $d$ is the desired filter output). Let $S$ be the ...
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What procedure to find the parameters of a given filter prototype to fit a desired frequency response?

To model the frequency response of a system, I am looking for a method to fit the response of cascaded bi-quad filters to the response of that system using an optimization algorithm. The $S$-domain ...
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7 votes
2 answers
419 views

High Dynamic Range FIR Filters

Related to this question on using the Windowing method for FIR filter design versus the optimized algorithms such as least squares (firls in MATLAB, Octave and ...
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2 votes
1 answer
58 views

How to find point of inflexion of a digital signal?

Let's say I would like to find a point of inflexion of a digital signal which has been gathered via sampling of a continuous time domain signal with sampling period $100\,\mu s$. The digital signal ...
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6 votes
1 answer
122 views

Noise Variance and Sampling in the Linear Regression Context

I am new to signal processing, so please bear with me. My question applies to any general problem of estimation from noisy measurements but I will like to understand this through a problem given here. ...
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Impacted of a conjugated filter

What is the effect of using a conjugated FIR filter? I have a use case where a weight vector, x, can be estimated using the least squares approximation: $$Ax=b$$ $$ A^HAx = A^Hb$$ $$ x = (A^HA)^{-1} ...
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2 votes
2 answers
56 views

Methods for time series estimation in time domain

I am trying to estimate the clean form of a time series, $u(t)$ that is corrupted by additive White Gaussian noise $w(t)$ at a particular SNR. The received signal is: $$y(t) = u(t) + w(t)$$ My first ...
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compressed sensing versus Lomb-Scargle

Say I have a signal that's the sum of only a few sine/cosine waves, and some noise, which has been measured at random times. I would like to find the frequencies of the waves. With this goal in-mind, ...
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1 vote
2 answers
190 views

Projection Matrix derivation to constrained optimization problem with Lagrange multiplier

I am trying to derive famous Projection operator as a constrained minimization problem for the least square problem. The question is as follows: Find $x$ minimizing $ (y-x)^T(y-x)$ subject to $x = H\...
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4 votes
1 answer
155 views

Frequency-domain deconvolution: "Direct" filtering vs "Wiener" filtering

Can someone help with clarifying the difference between two approaches to frequency domain "deconvolution: For the frequency domain problem: We want to find a filter $F(\omega)$ which will ...
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Apply window taper for selected window or to full data block in algebraic problem with known frequencies?

First, I'd like to introduce a problem. I try to solve a set of linear equations in LS (Least Squares) sense, i.e. Ax=y (LS) => A^TA x = A^T y. x is a vector I'm looking for, but y is a measured ...
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1 vote
0 answers
321 views

Recursive Least Square For Filtering

I just started doing research on Recursive Least Square for filtering noises such as sensors and dc motors noises. The only thing I've seen on the internet was Theoretical information about RLS but ...
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6 votes
1 answer
318 views

Image Restoration by Solving Constrained Least squares in Frequency Domain (Frequency Domain Filtering)

I am trying to implement the constrained least squares filtering as described in Rafael C. Gonzalez, Richard E. Woods - Digital Image Processing 3rd Edition Section 5.9. The equation (...
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2 votes
2 answers
103 views

Why should the last point be excluded when performing a least-squares fit of a periodic discrete time signal?

I fitted the function: f(t)=A_o+A_1 cos(wt)+B_1 sin(wt) to the following periodic discrete signal: ...
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1 vote
1 answer
61 views

The cost function of LS algorithm

I'm trying to understand the derivation of LS algorithm for channel estimation in OFDM. Could anyone explain why do we need complex conj transpose in the below equation?
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7 votes
2 answers
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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<...
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Questions on the Generalized Tikhonov Regularization

My first question is about the quadratic functional that is used in generalized Tikhonov regularization: $$\Psi(f)=\frac{1}{2}\|f\|^2_\Gamma=f^T\Gamma f.$$ In the above equation what does $\Gamma$ ...
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4 votes
1 answer
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Variational Regularization Method in Image Processing

I would like to understand better variational regularisation methods in image processing. In particular, the formulas in this image: Why formula (3.13)? In the notes that I read I cannot find ...
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2 votes
1 answer
92 views

Difference equation system identification

Suppose I have a difference equation modeling a vehicle like this: $$d[k+1]=d[k]+a\cdot u[k]+b,\tag1\label{eq}$$ where $d[k]$ is total distance traveled at time $k$, $u[k]$ is engine input at time $k$ ...
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Unable to estimate for AR model using OLS, Yule Walker and MLE

I am learning estimation methods following the book of Steven Kay, "Fundamentals of Statistical Processing, Volume I: Estimation Theory " Theory says that if the measurement noise is ...
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1 vote
1 answer
51 views

How to find the value of regularization parameter/s when having one or multiple priors

I am working on a image reconstruction framework, specifically interferometry. In simple words we have data that is pertubated by noise, say $$ V^o_i = V_i + \sigma_i $$ Where $V^o$ is a complex ...
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1 vote
1 answer
851 views

Building a FIR filter from an arbitrary frequency-magnitude response curve (eg. Least Squares fitting) [duplicate]

I'm trying to create a FIR filter from a magnitude equation, where my starting equation provides the magnitude (amplitude) between 0 and 1 for any given frequency in Hz. I posted the magnitude ...
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2 answers
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Simultaneously minimize and maximize two cost functions

I want to solve the following optimization problem, in which I have two cost functions $J_1 = \mathbf{w}^T R_1 \mathbf{w}$ and $J_2 = \mathbf{w}^T R_2 \mathbf{w}$, where $R_1$ and $R_2$ are covariance ...
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6 votes
2 answers
236 views

Quadratic Programming with Linear Equality Constraints

I need to solve an equality constrained minimization problem as give below $$\min_{\textbf{w}} \mathbf{w}^TR\mathbf{w} $$ such that $$X\mathbf{w} = \mathbf{1}$$ where $R\in \mathbb{R}^{n\times n}$ is ...
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1 answer
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Least Squares Filter Design: Deriving the Objective Function

I'm following the derivation in this paper A Comb Filter Design Using Fractional-Sample Delay to obtain the objective function for the least-squares filter design. N-order FIR filter: $H(z) = \sum_{...
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2 votes
0 answers
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Solving Sparse Model with given Dictionary Using LASSO

I was trying to solve a problem where the basis matrix contains the components of $\sin(nx)$, $\cos(nx)$, $\sinh(nx)$ and $\cosh(nx)$. Say the $n$ varies from 1 to 100. While solving the lasso linear ...
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1 vote
0 answers
28 views

How to find the solution of nonlinear least square (NLS) equation for freqeuncy estimation

I am struggling to understand the theory of parametric methods for power spectral estimations of line spectra. And I want to find the solution of nonlinear least square (NLS) method for estimating ...
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2 votes
2 answers
489 views

Solve Undetermined Linear System Using NumPy's `lstsq()` Function

I would like to understand what I am doing wrong here. I am trying to perform polynomial regression by minimizing the least squares, $||Au-y||^2$, where $y$ is the given data and $A$ is the matrix ...
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5 votes
1 answer
212 views

Use Recursive Least Square as an "Actual" Filter?

I am currently studying recursive least square (RLS) and as far as I understand, the setup is (for example) that we are given a process with uncertain parameters/noise and we want to adapt parameters ...
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1 vote
1 answer
64 views

Why is the concept of a "state covariance matrix" necessary in estimation?

I'm currently taking a course in optimal estimation (and it's still very early in the course). Much of our work is based around the idea of a measurement model $y=Hx + v$ This model assumes our ...
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4 votes
1 answer
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Jacobian Computation in Least Squares IIR Filter Design

Long time lurker and first time poster - but unfortunately I haven't had any joy untangling this on my own. I've been studying Mathias Lang's thesis, Algorithms for the Constrained Design of Digital ...
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4 votes
2 answers
263 views

System Identification with a Limited Bandwidth Input Signal and Region of Interest

Given a FIR filter $h[n]$. Its action can described as: $$ \mathbf{y} = \mathbf{H} \mathbf{x} \\ \mathbf{y} = \mathbf{X} \mathbf{h} $$ where $\mathbf{H}$ and $\mathbf{X}$ is a Toeplitz matrix. If $h$...
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1 vote
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Difference Between a 1st Order SG Filter And a Least Squares Moving Average

I have been studying SG filters and i recently found another filter which seem to be commonly used in financial data smoothing which is the least-squares moving average, this filter is also called ...
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5 votes
1 answer
603 views

Learning the Coefficients of Auto Regressive (AR) Model Using Least Mean Squares (LMS) Filter for Signal Prediction

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 ...
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1 answer
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Range Estimation Based on Distance Differences

It is a range estimation problem, as shown in the figure. The blue circles are the anchor node' positions, which are produced by one moving anchor (the moving direction is shown with black arrow). ...
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Non Linear Recursive / Online Least Squares

I am searching for a recursive or online non linear least squares algorithm. I want to spread the computation out as new data is sampled like in the linear Recursive Least Squares or the LMS. ...
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5 votes
1 answer
241 views

Equivalence of Maximum Likelihood (ML) and Discrete Fourier Transfrom (DFT) Peak Finding for Single Tone Estimation

My understanding is Maximum Likelihood and DFT Peak Finding for a single tone produce the same results assuming the ML is restricted to the same frequencies as the DFT. I was wondering if there was ...
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1 vote
2 answers
208 views

Solving a Linear Mean Square Estimation the Easy Way

I have an exercise which is quite trivial. However I got stuck and I'm not sure if this the end-result. I assume there has to be a way to get this result much quicker. Given are two randomly ...
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4 votes
1 answer
123 views

Linear Difference Equation and Method of Least Squares

I'm reading the book "Fault-Diagnosis Systems" by Isermann in the par. 9.2.1a. The author explains how to estimate the parameter of a linear difference equation using Least Squares. We start with a ...
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7 votes
4 answers
1k views

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 ...
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0 votes
1 answer
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Defining Model in Kalman for Getting Position Using

I am stuck at modeling a system model, i.e. getting my state vector and input vector for navigating just using navaid and ins (tactical). My guess is that position is my only state vector and INS ...
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2 votes
1 answer
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Adaptive LMS Algorithm MATLAB

I'm having some trouble implementing my LMS Adaptive Filter in MATLAB to separate wideband and narrowband signals from a voice signal. I'm using a delayed version of my input as a reference as well ...
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0 votes
1 answer
101 views

Equalizers with low data rate systems

In case of using equalizers with ZigBee systems, what type of fading does the channel show, flat or frequency selective, fast or slow? Is the inter-symbol interference (ISI) problem encountered in ...
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0 votes
1 answer
810 views

Recursive Least Square Adaptive Linear Equalizer

For the adaptive filter to work properly, a desired signal d(n) needs to be provided. The output from the equalizer y(n) is subtracted from d(n) to produce an error signal, which is used to adjust the ...
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2 votes
1 answer
738 views

Design of FIR Filters with Arbitrary Magnitude and Phase Responses

I found many information in this thesis "Algorithms for the Constrained Design of Digital Filters with Arbitrary Magnitude and Phase Responses",i want to understand it. This question is a ...
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4 votes
1 answer
167 views

Sequential Non Linear Least Squares Problem

I have the the following non-linear function, $$s(x;A_k,\mu_k,\sigma_k)=\sum_{k=1}^2 A_k \exp\left(\frac{-(x-\mu_k)^2}{\sigma_k^2}\right)$$ with unknown (but deterministic) parameters $A_k,\mu_k,\...
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5 votes
3 answers
438 views

Complex Least Squares Approximation

In the case of frequency domain FIR filter design, the error function given by : $$E(\omega)=H(e^{j\omega})-D(e^{j\omega}) \tag{1}$$ is a linear function with respect to the unknown filter ...
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4 votes
1 answer
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Why Isn't the ML Estimator (MLE) in MIMO Spatial Multiplexing Obtained by the Least Squares Solution?

In the simplest scenario of MIMO spatial multiplexing: $$\mathbf{y} = H\mathbf{s} + \mathbf{n}$$ where: $\mathbf{s}=[s_0,s_1,...s_{M-1}] \\\mathbf{y}=[y_0,y_1,...y_{N-1}]$ $\mathbf{n}=[n_0,n_1,......
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4 votes
2 answers
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Question About Kailath's Paper - An Innovations Approach to Least Squares Estimation Part I: Linear Filtering in Additive White Noise

I'm reading the paper at the link below and I was following it for about 2 pages until I hit a road block on the bottom of page 648 where the author says: putting together 9-11, we obtain and ...
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