Stack Exchange Network

Stack Exchange network consists of 175 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange

Questions tagged [filter]

The tag has no usage guidance.

0
votes
1answer
33 views

How can we determine the appropriate number of hidden layers, kernels in convolutional neural network (CNN)?

I have checked a lot of questions here and in other websites. What I concluded is that there is no rules for choosing the right number of hyper-parameters in CNN, all what can we do is just trying ...
0
votes
0answers
32 views

Noise reduction with known noise distribution

I have a time signal with a known noise distribution parameters (gaussian, sd is known). I would like to estimate the true value statistically and in the best case obtain a confidence interval. As I ...
1
vote
0answers
25 views

Time series filtering notation

I am looking at some suggested filters for tidal data but am having trouble understanding the notation. For example, Godin (1972) suggests a low-pass filter for tidal data that is a combination of 24-...
0
votes
0answers
37 views

Why is number of convolution filters usually powers of two? What's good for that?

I'm studying deep learning these days, I'm a..newbie I guess lol I noticed that there are many "powers of two" in lots of places.. For example, number of convolution filter, batch size etc. I'm ...
0
votes
0answers
22 views

How do convolutional neural networks deal with many filters during convolution?

I am unsure of how convolutional neural networks treat several filters. Many of the examples I have seen only have filter at a time, and that is intuitive for me. Look at the nice visual tutorial here:...
1
vote
0answers
44 views

Is there a filter function that performs similar to moving average but does not loose data?

I need to smooth a time series using a low pass filter. A simple moving average is working fine for me, however, using a moving average causes an inevitable loss of data a the beginning of the ...
0
votes
0answers
12 views

modeling trend and noise simultaneously

If I suspect that the series have a slow moving and fast changing components, one way to model is to first decompose the series into the trend and noise, perhaps, using the band pass filters or other ...
0
votes
0answers
14 views

Continuous-time Observation process in Filtering (why differential equation?)

Suppose we start with a stochastic dynamical system equation $$ dX_t = a_t(X_t)dt + dW_t $$ and we want to augment it with an observation process (noisy measurements) to get a continuous-time ...
1
vote
1answer
27 views

Partial spline. Reference

I have a well done and perfectly working protocol to smooth my experimental data. I do the following: I have a variable of size 1000. Iteratively I choose random 100 points and spline them using the ...
0
votes
0answers
8 views

Comparing discrete distributions when the sample set contains long streams of unique erroneous observations?

There is a reference dataset which is a discrete count over a set of names which produces a distribution $P$, and a set of names that are entered into a website as usernames which has a distribution $...
1
vote
0answers
61 views

Faster RCNN - Pyramid of Filters vs Pyramid of Anchors (Reference Boxes)

I'm reading faster RCNN paper now and trying to understand what is the difference between Pyramid of Filters and Pyramid of Anchors methods from the scale point of view. I mean if I use only one ...
0
votes
0answers
24 views

Update Class Probabilities using a Bayesian Filter

I am classifying images over time in categories such as office, bathroom, living room and so on. The idea is to use all these classification to categorize the room where a robot is. I want to use a ...
0
votes
1answer
30 views

Filter rows in r having same categorical value in all columns and also rows with all different categories [closed]

I am attempting to filter rows from following dataset where a,b and c give same answers, and also where a, b and c all give different answers from a category of 3 answers. id A B C X1 X2 ...
9
votes
2answers
1k views

Wouldn't multiple filters in a convolutional layer learn the same parameter during training?

Based from what I have learned, we use multiple filters in a Conv Layer of a CNN to learn different feature detectors. But since these filters are applied similarly (i.e. slided and multiplied to ...
1
vote
0answers
50 views

Great ways to identify adult content in text

What are some good ways to identify adult content in text. It is definitely a text classification problem, but how do we handle words that are spelt like @$$.
1
vote
2answers
564 views

Removing gaussian noise from a time-series data

I have a noisy time-series data (Figure 1). As you can see the variance in this data set is very high and the "Gaussian noise" needs to be removed for me to analyze this signal. Normally we apply a ...
0
votes
0answers
11 views

Type of filter to use to select high frequency in a non continuous time serie data

I am trying to study correlation between many time series of electricity consumption ( unit voltage in time ). I have several problems, the data isn't continuous, I only have observation each 15 min, ...
0
votes
0answers
43 views

In prewhitening, should we develop an ARIMA(p,q,d) for X but use only ARI(p,q) as the filter?

According to the answer in this question by IrishStat, the reason that you pre-whiten X is to identify a filter that can transform Y and X into y and x where x is white noise. Assume that X is ...
1
vote
0answers
14 views

checking the quality of filtering of a temporal series

I have many temporal series of satellite data. I decided to smooth that using Savitzky-Golay filter implemented in R using the "signal" package. I could use also other smoothing algorithms, that's ...
0
votes
0answers
18 views

Appropriate Feature Selection model for Mass Spectrometry data

I have a cancer patients data which consists of more than half million features and my task is to apply feature selection algorithm to extract the most relevant features from it. My question is which ...
1
vote
0answers
149 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 ...
1
vote
2answers
92 views

some examples of filtering the noise out of a data set

I have a data set which measures 60 data points in a second (60Hz). Clearly, I do not really need all 60 points in one second since this only generates some noise. ABOUT MY DATA: So my data sets ...
1
vote
1answer
181 views

Denoising technique for signal with beforehand known shape (linear and exponential)

I have a noisy signal which is linear and then exponential. I know the type (Gaussian additive noise) and degree (0.01) of noise. Part of the challenge is determining when the signal changed from ...
2
votes
1answer
56 views

What are the downsides of having a large number of convolutional filters

This question is purely about a single convolutional layer in a neural network - not about the number of layers. Aside from computational time what are the downsides of increasing the number of ...
3
votes
0answers
75 views

Who says trading data are noisy?

We try to denoise our time-series and model inputs with a plethora of methods like Kalman filters, EMA, Kernel filters, Splines, Beziers, etc. But who came up with a theory that trading data is noisy ...
0
votes
2answers
677 views

SMC (Particle Filtering) code [closed]

Does anyone know where I can find particle filtering code for R? In particular I'm looking for code for filtering a forward-rate curve.
1
vote
1answer
4k views

Convolutional neural network with images that have color channels

According to this guide, when applying a kernel to an input volume, the kernel always has to have the same depth as the input volume. When using images, I figured, that means the color channels. ...
2
votes
2answers
132 views

Savitzky-Golay … integrator?

Background: Savitzky-Golay filters (yes they have other names) are robust estimators of slope. Where a small noise can substantially damage the slope estimate of textbook finite difference methods, ...
1
vote
0answers
49 views

Identify this statistical filter?

I have a piece of code that takes a noisy data set and uses some sort of statistical filter to plot a trend line over the noisy data. The original author of the code no longer works at my job, so I ...
1
vote
1answer
70 views

Isn't every linear filter a linear time invariant (LTI) filter?

I'm using the following definition for a linear time invariant digital filter: "A digital filter L that transforms an input sequence $\{ x_{t} \}$ into an output sequence $\{ y_{t} \}$ is called a ...
3
votes
2answers
712 views

Stationarity of AR(1) process, stable filter

This section of the Wikipedia article about the Autoregressive Model reads: An AR(1) process is given by: $$X_t = c + \varphi X_{t-1}+\varepsilon_t$$ where $\varepsilon_t$ is a white noise process ...
1
vote
2answers
79 views

Filtering disturbances from time series

Lets suppose that time series of the following building climate related measures are given for a small building: Solar radiation Outdoor air temperature Heat supply Indoor air temperature The ...
3
votes
0answers
22 views

Prove that a symmetric filter preserve an p-order trend

Let the centered filter $\Theta (L)=\theta _{-m}L^m+...+\theta _{-2}L^2+\theta _{-1}L+\theta _{0}+\theta _{1}L^{-1}+\theta _{2}L^{-2}+...+\theta _{m}L^{-m}$ where $\theta _{-m}+...\theta _{-2}+\...
0
votes
1answer
195 views

How to explain exponential plus Gaussian noise

I have some noisy signal. When I substract real (for calibration it is known) or filtered signal I get residuals. When I plot distribution of these residuals I see that it is sum of exponential and ...
1
vote
0answers
47 views

Introduction to filtering - Kalman filtering

I would like to make a preamble and then introducing the Kalman filter in a work I am writing. In your opinion which are the topics I have to cite? Do you think I should cite Kolmogorov and Wiener ...
1
vote
0answers
29 views

Savitzky-Golay with switching between scales based on slope

I am having fun with Savitzky-Golay (aka H-P, W-H) and I am bumping into limits of the filter. It makes me want a better filter. Is there a filter that adjusts filter order based on "slope" but ...
1
vote
1answer
106 views

Why is it harder to obtain diagnostic knowledge $p(h\mid z)$ than causal knowledge $p(z\mid h)$? [closed]

Causal knowledge is $p(z\mid h)$, i.e. the probability that a certain state $h$ causes a certain state of the observable variable $z$. Diagnostic knowledge on the other hand refers to the knowledge we ...
3
votes
0answers
144 views

Deseasonalizing a time series using a Wiener-Kolmogorov filter

I am trying to eliminate seasonality from a time series using Wiener-Kolmogorov filter, I am following the methodology explained in here this paper about signal extraction which is the same followed ...
5
votes
1answer
1k views

Why taking the first difference is the same as an AR(1) filter?

Today, my professor said that for highly correlated time series, taking the first differentiation is like applying an AR(1) filter.. Unfortunately I a was not able to ask him after the lecture. I am ...
3
votes
2answers
217 views

How can I detect when a key was pressed with accelerometer or gyroscope data?

I have a dataset (~20k samples) of sensor data gathered from a smartphone. What I want to do with it is to detect those spikes you can see in the graphs below. They occur when the user presses a ...
2
votes
0answers
67 views

Noise estimation in LTE using bandpass filter

Can noise estimation in LTE be done using bandpass filter? As per my study in wireless systems to estimate noise power, if pilot sequence is known is done as |y(k)-p(k)h(k)|^2, where p(k) is pilot ...
2
votes
1answer
575 views

How can I filter out GPS “spidering” from tracks created when user is stationary?

We collect vehicle mileage data from GPS loggers (based on a 5 second sample of location) and need an accurate measure of the mileage travelled. However what's caught us out is that some vehicles ...
7
votes
2answers
2k views

Filtering vs Smoothing in Bayesian Estimation

I am facing a posterior distribution in a MCMC application that aims to sample an unobservable variable $x=\{x_t\}_{t=0}^{T}$ given an observed series $y=\{y_t\}^T_{t=0}$. However, the conditional ...
2
votes
1answer
2k views

Using Hodrick-Prescott filters for analyzing and forecasting business time series

I have many time series data at work. Some are annual, some are quarterly, and some are monthly. I am exploring Digital Signal Processing (DSP) as a complementary approach to ARIMA and other methods. ...
0
votes
1answer
314 views

Inverse of exponential smoothing

Suppose that a time series $s_t$ it is known to be obtained via exponential smoothing of an underlying signal $x_t$, that is $$ s_{0}= x_0 $$ and $$ s_{t} = (1-\alpha)\,x_t+\alpha\,s_{t-1}. $$ ...
0
votes
1answer
185 views

Fast Gaussian Filtering Using a Permutohedral Lattice

I'm trying to implement http://www.dabi.temple.edu/~zoran/papers/KostaAAAI13.pdf but am stack at understanding equations 10) and 11). They claim that the sum of the Gauss kernel multiplied with the ...
1
vote
0answers
655 views

Signal Processing Steps for Raw Accelerometer Data

A project I am engaged with involves taking raw accelerometer data (in g's ) and analyzing for the existence of tremors (the accelerometer is attached to an individuals hand). I am relatively new to ...
1
vote
0answers
107 views

Recursive Bayesian estimation for the coefficients of a convex combination

I'm given a sequential measurements of vectors $\vec{v}_t\in R^{K+1}$ such that $v_{t,0}$ is a convex combination of $\{v_{t,k}\}_{k\ge 1}$ (i.e. $v_{t.0}=\sum_{k\ge 1}{w_{t,k}v_{t,k}}$ for some ...
2
votes
1answer
45 views

5 low signal-to-noise measurements of same signal, know noise distribution and signal distribution. Recover?

I have 5 measurements of $x(t)$ at each instance in time, all contaminated with Gaussian noise. My signal-to-noise ratio is bad. \begin{align} y_1(t)=x(t)+n_1(t)\\ y_2(t)=x(t)+n_2(t)\\ y_3(t)=x(t)+...
2
votes
1answer
442 views

Savitzky-Golay (aka Hodrick–Prescot or Whittaker-Henderson) vs. Kernel

Is there a clear analytic link from Kernel smoothing, particularly the Nadaraya–Watson estimator, (S-G, H-P, or W-H) smoothing filter? The "filter" is called by different names in different fields ...