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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18 views

Ways to quantify the fluctuations in the curve [closed]

I have a data frame as shown via this link: data and am trying to find a way to interpret my data so that I know at which frequency the power is the largest. They are force vs. distance as I was ...
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Smoothing contours for contour analysis for character recognition

I am making a character recognition library using contour analysis. Contours are sequencies of complex numbers X + j*Y (in fact in contour analysis they are defined ...
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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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Following a smoothing filter of a biological signal

)Following a smoothing filter of a biological signal. y[n] = Ay[n − 1] + Bx[n − 2] Please find the transfer function in the z-domain and find the impulse response function of this filter.
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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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107 views

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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1answer
82 views

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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198 views

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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188 views

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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80 views

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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1answer
30 views

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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202 views

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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79 views

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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91 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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how to do smoothing a linear noise adc signal to a exponencial curve to increase and logarithmic to decrease

I am studying methods of signal smoothing obtained in an Analog Digital converter that is operated by a common potentiometer that generates a certain noise, such potentiometer is linear and I cannot ...
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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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169 views

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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148 views

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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251 views

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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189 views

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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37 views

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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1answer
30 views

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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161 views

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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1answer
330 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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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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123 views

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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97 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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1answer
105 views

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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52 views

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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66 views

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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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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685 views

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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1answer
211 views

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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221 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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94 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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1answer
143 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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131 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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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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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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169 views

What Are Different Approaches to Realize a Gaussian Blur (Smoothing) Step on an Image? [closed]

Could some review some methods to apply Gaussian Filter (Blur) on an image besides the direct one using Truncated FIR (classic convolution with Truncated Kernel) approximation?
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EKF smoothing for prediction at t=0 when no there is no measurement

I have a simple first-order reaction batch system for which I have some discrete measurements ($0<t_{k}\le t_{endbatchsample}$). I have an initial guess for $x_0$ and $P_0$ and from here I ...
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248 views

Does this Signal Smoothing algorithm have a name?

We are reverse engineering some 20 year old software. Original developers were laid off years ago, and cannot be found. In this code, there is a signal that is getting smoothed as follows: $P_{new} ...
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338 views

Make a signal that fits another the best possible with a limitation in the 2nd derivative

Consider this step function: The signal that "fits" this should look like the following (in green): The corners are now smooth because the maximum second derivative allowed is not infinite anymore. ...
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437 views

How to smoothen signal with missing values before differentiation?

I want to differentiate a noisy signal with many, randomly located, missing data values. Which smoothing techniques should be applied before differentiating the signal? I have a velocity signal at ...
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643 views

How to smooth (or interpolate) phase of FFT and reduce data points

I am writing some code for audio analysis, and have currently got two signals with FFT performed on them. I get the phase of my complex array by using: ...
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456 views

Estimate standard deviation of random-walk using Kalman filter

I'm new to Kalman filters so this might be a stupid question. I created a Kalman filter that takes in time series observations and estimates the mean of that time series. This is simply modeling a ...
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2k views

How to Mesure the smoothness of a signal

so how can i determine if a signal is smooth or not ? And if its possible to get something indicating the level of the smoothness of my signal. I looked at the r-squared and hurst exponent but i ...
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67 views

Should zero element be considered to calculate mean when smoothing spectrogram by window?

My (mass spectrometry) spectrogram does not measure the intensity constantly. I obtain the spectrogram, for example, ...