Questions tagged [smoothing]

Smoothing a signal or data set approximates the data to reveal patterns and exclude noise, fine-scale structure and rapid changing phenomina.

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Applying a window to a signal

How can I Gaussian or Bartlett window to a signal? On the other hand, is it a good way of smoothing signals? If not what are the differences between smoothing and windowing?
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2 votes
1 answer
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What is the outcome of applying a derivative on X and Y for an image? and Other Gaussian Questions

I've been diving into smoothing kernels and I came up with a lot of questions that I haven't been able to find in the internet. If you can I'd appreciate the help :) (Capitals and bold were used for ...
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7 votes
2 answers
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How to Deal with Outliers in Measurement of a Simple Model of Kalman Filter

I am trying to find the one-dimensional velocity of a car based on position measurements, similar to the Wikipedia article. The car moves at almost constant speed and I am mostly interested in ...
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Signal filtering with physical limitations and estimated STD

I have a prediction mechanism that predicts some signal value. Generally the prediction look like this: The are some ranges of systematic error and I cannot do anything with this. But in many points ...
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Spectrum Smoothing

I recently stumbled upon this GNU Radio flow graph which smooths spectrum. Block parameters are seen in image attached below. Also visually results doesn't change if I take out "Keep 1 in N" ...
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How to smooth wiener deconvolution result in Python?

I'm wondering if it is possible to smooth the estimated response from a Wiener deconvolution in order to have a better representation of the original signal and to remove the side lobes. (Here an ...
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How to measure smoothness of a signal

Lets say I have two signals with a different number of data points - a step function and a smooth spline as you can see below. What is mathematical operation I can use to quantify the "smoothness&...
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1 vote
1 answer
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Constrained interpolation/smoothing of multi-dimensional time series

Consider an $N$ dimensional time series $x_i(t),~i\in\{0,1,\cdots, N-1\}$ where $x_i(t)$ is smooth. It turns out that for all $t$: $x_i(t)>x_{i-1}(t)$. The multi-dimensional series is sampled at ...
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Peak detection in noisy waveforms

I have a set of 1-dimensional time-series, a subset of which contain either one or two peaks, and the remainder of which are pure noise. I've smoothed these data by ...
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Is there a technical term for smoothing or flattening the floor of an amplitude envelope?

I am working with the speech envelope, and I have been trying to make it act a little more like a bilevel signal by exaggerating the peaks and flattening out the floor. I detrended and smoothed my ...
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Is there any complex-valued function used to smooth signals?

To obtain a smoother signal, we usually convolve the original signal with a real-valued kernel function, such as Gaussian and Top-hat. Is there any complex-valued kernel function to smooth signals?
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Calculate moving RMS with exponential averaging

This is moving RMS, now how to add exponential averaging in this df['signal'].rolling(21*24*60).apply(lambda x: np.sqrt(x.mean()))
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Data smoothing in temperature measurements from MLX90614 BCC IR sensor

I am trying to measure temperature with the MLX90614 BCC IR sensor for my project, and I am having problems with my precision requirement. I had taken data for 1 second then took the mean of these ...
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Choose the right Sigma for Gaussian filter

I have the following problem: I have a time series with counted data. I now want to smooth it using a Gaussian low-pass filter. Is there a method to determine the sigma value? The window should have a ...
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Box function signal filtering in python

I am trying to produce a box function filter of a signal in python. I expected to find this functionality in scipy.signal, but I can't find any solutions. What I am trying to do is this. I have 2 ...
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Smoothing power spectrum by convolution with boxcar function

I am trying to smoothing a signal's power spectrum by convolving the spectrum with a boxcar function in frequency domain. However, the result is obviously not what I expected: original two frequency ...
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Smoothing peak spectra in time domain

I would like to smooth amplitude spectra of signals around their peak frequencies. I could perform FFT, find the peak frequency, and smooth around the peak in frequency domain, then inverse FFT back ...
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Deriving a Kalman Filter Equation for a Linear Gaussian Filtering Model with Non Zero Mean Noise

I am trying to answer an exercise question from the book Simo Sarkka - Bayesian Filtering and Smoothing. The question is: Does anyone know if there is a resource that has the solutions for this book?
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4 votes
1 answer
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The Effect of the Standard Deviation ($ \sigma $) of a Gaussian Kernel when Smoothing a Gradients Image

I am trying to understand why smoothing an image with a gaussian kernel of different sigma values and then computing the gradients of the smoothed image leads to "thicker" trails. In the ...
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1 answer
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What is the point of smoothing an FFT or spectral density plot, and how does that affect the noise floor?

It appears that smoothing the FFT or spectral density plots of a noisy signal is a common practice. I see that common tools like MATLAB and Python have functions built in to their FFT tools to do just ...
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Is it applicable to implement a cascaded moving average filter with variable window on real-time?

I am using a 3-pass cascaded moving average filter for smoothing noisy data. I applied some optimization algorithms to determine the optimal length of the MAF window. For different amplitudes of data ...
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1 answer
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Error introduced by smoothing filter at the end of a processing block

I'm running analysis on a multichannel audio signal and due to the size have decided to process it in blocks (my computer doesn't have enough memory to process it in one go). Some of the data produced ...
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6 votes
1 answer
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A Simple Algorithm to Filter / Smooth / Denoise a Noisy Staircase Graph

Is there a way to remove the noise and smooth the graph into a staircase graph.
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1 answer
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Possible to get transfer function coefficients from window?

I am hoping to use scipy.signals.filtfilt() to smooth some signals in Python, and wanted to build the filter based on a window like a hanning window or whatever. E....
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6 votes
3 answers
114 views

Reversing the Order of Operators for Edge Detection?

Usually, for edge detection, we perform smoothing and then pass it through difference filter. What if application of difference filter happens first and then smoothing. How the math behind the same ...
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1 answer
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I want to get tilt sensor value for a given time t_0, but the tilt sensor data points are discrete. How do I interpolate between the discrete points?

I have 3-dimensional readings from a tilt sensor (specifically these are rotational angles about X, Y, and Z axes) over time. Let's call these angles S. I want to infer S at a specific time t_0, but ...
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How to properly smooth the phase of a spectrum (or any unit-complex function)

I want to smooth the phase of a measured (transfer) spectrum without destroying unit-complexity of the phase factor. Suppose $$f:\mathbb{R}\to \mathbb{C}\qquad , \qquad f(\omega)=r(\omega)\cdot {\rm e}...
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Smooth signal with Hanning

I have an acceleration record and i want to smooth it's spectrum by using a hanning window with Bandwidth=0.5 Hz. How could i do that? Example in python/matlab will be appreciated!
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2 answers
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Confused in Smoothing a signal in the Frequency domain

First of all i am new in DSP, so i have no solid education in the field. I have convert my time domain acceleration-seismic data to frequency using DFT and i am trying to smooth the DFT data, in ...
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3 answers
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How do you do signal averaging on a realtime data?

Smoothing algorithms implemented by me Exponential smoothing - https://www.openprocessing.org/sketch/771368 Moving Mean - https://www.openprocessing.org/sketch/540696 For example - a1+a2+a3+a4+... ...
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Smoothing a discrete function with point wise variances

In Stark's Introduction to numerical methods [1970] it suggests fitting local polynomials to smooth discrete data before the Fourier transform using least squares minimisation. This gives the ...
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1 answer
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Can you predict how long a discontinuity will take to reach its target if it is low pass filtered at a certain frequency?

Let's say you have a signal that relatively slowly rises from 0 to 1, then suddenly from one sample to the next drops back to 0, creating a sharp discontinuity. Let's say you run it through a one pole ...
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Filterpy Kalman Filter batch processing with multiple measurement sources

In pythons module for kalman-filtering, filterpy, there is a function batch_filter() to batch filter a list of measurements that then can be used for RTS-smoothing. ...
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4 votes
1 answer
642 views

Kalman Filter EM Estimation of Covariances

The question might be very simple, but I get a strange result from Kalman Filter. Let us consider the simplest state-space model, the random walk plus noise: $$ y_{t} = x_{t} + \varepsilon_{t}\\ x_{t} ...
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Slew Rate Filter With Different Smoothing Factors in Each Direction

I'm smoothing the output of an ADC with a simple first order low pass filter. Of course the smoothing rate is the same whether the signal is rising or falling. Preferably the smoothing rate needs to ...
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2 votes
0 answers
170 views

Algorithm for smoothing the output of an object detector operating on a video?

Please could you point me towards an algorithm that takes a series of object detections performed on a frame by frame basis as input and outputs a filtered series of object detections in which the ...
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1 answer
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Selected bin oscilation in STFT

I am looking for a noisy signal using STFT. My window length is 128 and I am using 75% overlap. I am using a Hanning window before running the FFT process. I am using Quinn's 2nd estimator for ...
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135 views

temporal smoothing: FWHM of Gaussian kernel vs. window length of moving average

Suppose in one case I convolve Gaussian kernel with FWHM=10 samples. I would like to compare the result with moving average. My question: should I take the moving average window also 10 samples? In ...
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1 answer
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Continuous time double exponential filtering in state space form?

I'm trying to determine the continuous time formulation of the double exponential filter so that I can adapt it more flexibly for my particular problem. Typically, this model is expressed as a pair ...
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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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1 vote
0 answers
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Implementing Edge Preserving Diffusion (Anisotropic Diffusion)

I am trying to implement edge preserving diffusion. Recall the general diffusion equation to be: $$\DeclareMathOperator{\Div}{div}\delta_t u = \Div(g \nabla u)$$ Where $g$ is the speed of the ...
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7 votes
1 answer
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The Meaning of the Terms Isotropic and Anisotropic in the Total Variation Framework

The isotropic TV is defined as the estimation of 2-norm of gradients $\sqrt{(y_{i+1,j}-y_{i,j})^2+(y_{i,j+1}-y_{i,j})^2}$, while the anisotropic TV is defined as the estimation of 1-norm of gradients $...
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How to extract a smooth contour from a set of points in 3D?

I am trying to segment a 3D volume. The outcome of all my volume segmentation algorithms is a set of candidate points in 3D space. Now I need to smooth this point cloud and fit a closed surface it. My ...
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2 votes
1 answer
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Classifying and filtering out noise from zero crossings

Note: I know absolutely nothing about zero crossings nor signal processing in general. However, I am doing programming exercises that require them. I've searched around but I cannot understand most of ...
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5 votes
1 answer
300 views

Fast Recursive 1D Signal Smoothing - IIR / Auto Regressive Implementation of Gaussian Smoothing

I have just begun to dive into the field of signal processing, but there is the need to program a digital filter, that has to smooth a realtime signal from a sensor device. As far as I know, in my ...
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1 vote
0 answers
153 views

Modified Bryson-Frazier (MBF) smoother explain

I'm reading about MBF smoother on Wikipedia. I'm confused of the quantity $\hat{\lambda}_k$ and $\tilde{\lambda}_k$. What does they really mean intuitively ? Why the update formula has the form $\...
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3 votes
1 answer
240 views

Chromatogram peak detection - bunching vs others?

Reading presentations from existing tool providers I noticed that in order to detect peaks they first use bunching (average N points) and then use slope and curvature to detect peaks. I'm guessing ...
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1 vote
0 answers
188 views

Are there any applications using absolute Savitzky-Golay filter to smooth data and preserve non-negative properties?

I want to smooth peaks for non-negative matrix factorization (NMF). Since Savitzky-Golay has polynomial smoothing, I think it is good for narrow peak shape in my signal profile. But NMF needs to be ...
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12 votes
2 answers
7k views

Why should an image be blurred using a Gaussian Kernel before downsampling?

I recently read that before downsampling an image, it should be blurred using a Gaussian Kernel. This way, the downsampled image is better than just picking a single pixel out of a NxN block or ...
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11 votes
3 answers
8k views

Savitzky–Golay filter vs. IIR or FIR linear filter

A traditional IIR / FIR filter (lowpass to remove the high freq oscillations), e.g. moving average, or a Savitzky-Golay filter can all be useful to smoothen a signal, such as an envelope signal: ...
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