scholarly journals Algorithms of distortion compensation for broadband signals propagated through satellite ionospheric channels.

2021 ◽  
Vol 2021 (6) ◽  
Author(s):  
V.V. Batanov ◽  
◽  
L.E. Nazarov ◽  
◽  
Keyword(s):  
Computer Simulations ◽  
Frequency Band ◽  
Digital Signal ◽  
Computational Procedure ◽  
Linear Filter ◽  
Linear Filtering ◽  
Digital Signals ◽  
Distortion Compensation ◽  
Complex Envelope ◽  
Wideband Signals

Methods for describing of digital signal complex envelope distortions due to influence of satellite ionosphere radiolines based on linear filtering methods are presented. Distortions of the phase-frequency characteristics of the digital signal envelopes due to the dispersion properties of the ionosphere cause time scattering and the occurrence of intersymbol interference, which reduce the reliability of communication. This determines the relevance of the development of the computational procedure for processing digital signals that reduce the effectiveness of this type of interferences. The descriptions of the algorithms for compensation of these distortions based on the use of the broadband pilot-signals and the formation of an inverse linear filter are given. A useful property of the considered pilot-signals is the coincidence of their structure (frequency band, envelope type, manipulation law) with the structure of information digital signals. By means of computer simulations of this algorithms, the possibility of almost complete compensation of the considered distortions of wideband signals is shown.

scholarly journals Algorithm of phase-frequency distortion adaptive compensation for broadband signals during propagation through transionospheric channels.

2021 ◽  
Author(s):  
V.V. Batanov ◽  
◽  
L.E. Nazarov ◽  
◽  
Keyword(s):  
Information Systems ◽  
General Concept ◽  
Linear Filter ◽  
Adaptive Compensation ◽  
Digital Signals ◽  
Distortion Compensation ◽  
Wideband Signals ◽  
Acceptable Quality ◽  
Shift Keying ◽  
Computational Procedures

The models of distortions of digital broadband signals during their propagation through transionospheric channels which are equivalent to a linear filter with an impulse response determined by a number of parameters, in particular, the central frequency of the signals, are presented. Distortions of the phase-frequency characteristics of digital broadband signals due to the dispersion properties of the ionosphere causes time scattering and the appearance of interference noise which reduces the reliability of information systems and with certain characteristics of the radiochannel destroys their operation. This determines the relevance of developing computational procedures for processing digital signals that reduce the effectiveness of this type of interference, a characteristic property of which is the linear dependence of their power on the power of information signals. The description of the algorithm for adaptive compensation of these distortions based on the use of information signals and the formation of an inverse filter is given, which corresponds to the general concept of "blind" processing. The possibility of the considered distortion compensation for digital wideband signals with phase shift keying and achievement of probabilistic characteristics of erroneous reception providing an acceptable quality of a radiochannels for information systems has been shown by means of computer simulations.

DESIGNING OF ALL-OPTICAL TRI-STATE LOGIC SYSTEM WITH THE HELP OF OPTICAL NONLINEAR MATERIAL

2008 ◽  
Vol 17 (03) ◽  
pp. 315-328 ◽  
Author(s):  
TANAY CHATTOPADHYAY ◽  
GOUTAM KUMAR MAITY ◽  
JITENDRA NATH ROY
Keyword(s):  
High Speed ◽  
Optical Switch ◽  
Digital Signal ◽  
Optical Signal ◽  
Nonlinear Material ◽  
Digital Signals ◽  
Photonic Networks ◽  
Optical Nonlinear Material ◽  
All Optical ◽  
Logic Operations

Nonlinear optics has been of increased interest for all-optical signal, data and image processing in high speed photonic networks. The application of multi-valued (nonbinary) digital signals can provide considerable relief in transmission, storage and processing of a large amount of information in digital signal processing. Here, we propose the design of an all-optical system for some basic tri-state logic operations (trinary OR, trinary AND, trinary XOR, Inverter, Truth detector, False detector) which exploits the polarization properties of light. Nonlinear material based optical switch can play an important role. Tri-state logic can play a significant role towards carry and borrow free arithmetic operations. The principles and possibilities of the design of nonlinear material based tri-state logic circuits are proposed and described.

Study on Enhancing Terminal Identification in Track and Field Using Digital X-Ray Photography Image

2014 ◽  
Vol 989-994 ◽  
pp. 3851-3855
Author(s):  
Guang Jin Lai
Keyword(s):  
Motion Capture ◽  
Clustering Algorithm ◽  
Digital Signal ◽  
Human Head ◽  
Track And Field ◽  
Image Clustering ◽  
Digital Signals ◽  
Recognition Method ◽  
One Dimensional ◽  
X Ray

Digital X-ray photography technology is under the control of the computer, to use one-dimensional or 2D X-ray detector to convert the captured image into digital signals directly to using image processing technology. It can realize the function of image analysis. We introduce X-ray photography technology into the terminal identification in track and field, and use the clustering algorithm to improve computer image clustering algorithm. Through capturing the digital signal of human head, arms and legs, it enhances the terminal recognition method in track and field. Finally we use MATLAB to calculate the captured image value of X-ray photography. Through calculation, motion capture and recognition of X-ray image are enhanced obviously. It provides a theoretical basis for researching on motion capture technology in track and field.

Signal quantitative analysis using customizable perfect-translation-invariant complex wavelet functions

2014 ◽  
Vol 12 (04) ◽  
pp. 1460010 ◽  
Author(s):  
Hiroshi Toda ◽  
Zhong Zhang
Keyword(s):  
Quantitative Analysis ◽  
Frequency Band ◽  
Wavelet Transforms ◽  
Wavelet Coefficient ◽  
Discrete Wavelet ◽  
Digital Signals ◽  
Orthonormal Wavelet ◽  
Translation Invariant ◽  
Fast Calculation ◽  
Complex Wavelet

In this paper, we introduce several methods of signal quantitative analysis using the perfect-translation-invariant complex wavelet functions (PTI complex wavelet functions), which are used in our proposed perfect-translation-invariant complex discrete wavelet transforms (PTI CDWTs) and can be designed by customization. First, using PTI complex wavelet functions, we define the continuous wavelet coefficient (CWC). Next, using orthonormal wavelet functions in the classical Hardy space, we analyze the CWC, and show that, using a CWC, we can measure the energy of a customizable frequency band, and additionally, using numbers of CWCs, we can measure the energy of the whole frequency band. Next, we introduce the fast calculation method of CWCs and show the applicability of the PTI CDWTs to digital signals. Based on them, we introduce some examples of signal quantitative analysis, including the methods to obtain instantaneous amplitude, instantaneous phase and instantaneous frequency. Additionally, we introduce the energy measurement of the whole frequency band using the PTI DT-CDWT, which is one of our proposed PTI CDWTs.

A single digital linear filter for computations in electrical methods—A unifying approach

Geophysics ◽  
1984 ◽  
Vol 49 (7) ◽  
pp. 1115-1118 ◽  
Author(s):  
U. C. Das
Keyword(s):  
Linear Filter ◽  
Linear Filtering ◽  
Electrical Measurements ◽  
Domain Integral ◽  
Electrical Methods ◽  
Single Formula

A major contribution to the interpretation of electrical measurements was made with the application of digital linear filtering introduced by Ghosh (1970, 1971a, b). This rendered the computations easy and fast. In a recent publication, I showed (Das, 1982) that the filters for computing responses for any electrode or coil configurations employed in electrical methods could be derived easily from stored basic spectra of the two filter functions, namely, [Formula: see text] and [Formula: see text]. One has to multiply the stored spectra by simple factors to arrive at the required spectra. I show here that a simple mathematical manipulation transforms a [Formula: see text] domain integral into its corresponding [Formula: see text] domain integral, thereby leading to the use of a single [Formula: see text] filter for a variety of computations in electrical methods.

scholarly journals Modular preprocessing pipelines can reintroduce artifacts into fMRI data

2018 ◽  
Author(s):  
Martin A. Lindquist ◽  
Stephan Geuter ◽  
Tor D. Wager ◽  
Brian S. Caffo
Keyword(s):  
Fmri Data ◽  
Linear Filter ◽  
Linear Filtering ◽  
Linear Filters ◽  
Data Set ◽  
Temporal Filtering ◽  
Global Signal ◽  
In Series ◽  
Band Pass ◽  
Fmri Analysis

AbstractThe preprocessing pipelines typically used in both task and restingstate fMRI (rs-fMRI) analysis are modular in nature: They are composed of a number of separate filtering/regression steps, including removal of head motion covariates and band-pass filtering, performed sequentially and in a flexible order. In this paper we illustrate the shortcomings of this approach, as we show how later preprocessing steps can reintroduce artifacts previously removed from the data in prior preprocessing steps. We show that each regression step is a geometric projection of data onto a subspace, and that performing a sequence of projections can move the data into subspaces no longer orthogonal to those previously removed, reintroducing signal related to nuisance covariates. Thus, linear filtering operations are not commutative, and the order in which the preprocessing steps are performed is critical. These issues can arise in practice when any combination of standard preprocessing steps—including motion regression, scrubbing, component-based correction, global signal regression, and temporal filtering—are performed sequentially. In this work we focus primarily on rs-fMRI. We illustrate the problem both theoretically and empirically through application to a test-retest rs-fMRI data set, and suggest remedies. These include (a) combining all steps into a single linear filter, or (b) sequential orthogonalization of covariates/linear filters performed in series.

Fundamentals of Multirate Systems

2011 ◽  
pp. 1601-1605
Author(s):  
Gordana Jovanovic Dolecek
Keyword(s):  
Signal Processing ◽  
Integrated Circuits ◽  
Digital Signal Processing ◽  
Rapid Development ◽  
Sampling Rate ◽  
Digital Signal ◽  
Digital Signals ◽  
Multiple Sampling ◽  
Multirate System ◽  
Rate Conversion

Digital signal processing (DSP) is an area of science and engineering that has been rapidly developed over the past years. This rapid development is a result of significant advances in digital computers technology and integrated circuits fabrication (Mitra, 2005; Smith, 2002). Classical digital signal processing structures belong to the class of single-rate systems since the sampling rates at all points of the system are the same. The process of converting a signal from a given rate to a different rate is called sampling rate conversion. Systems that employ multiple sampling rates in the processing of digital signals are called multirate digital signal processing systems. Sample rate conversion is one of the main operations in a multirate system (Harris, 2004; Stearns, 2002).

scholarly journals The Impact of Linear Filter Preprocessing in the Interpretation of Permutation Entropy

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 787
Author(s):  
Antonio Dávalos ◽  
Meryem Jabloun ◽  
Philippe Ravier ◽  
Olivier Buttelli
Keyword(s):  
Moving Average ◽  
Permutation Entropy ◽  
Linear Filter ◽  
Type I ◽  
Linear Filtering ◽  
Linear Filters ◽  
Ordinal Information ◽  
Specific Frequency ◽  
The Impact ◽  
Specific Contribution

Permutation Entropy (PE) is a powerful tool for measuring the amount of information contained within a time series. However, this technique is rarely applied directly on raw signals. Instead, a preprocessing step, such as linear filtering, is applied in order to remove noise or to isolate specific frequency bands. In the current work, we aimed at outlining the effect of linear filter preprocessing in the final PE values. By means of the Wiener–Khinchin theorem, we theoretically characterize the linear filter’s intrinsic PE and separated its contribution from the signal’s ordinal information. We tested these results by means of simulated signals, subject to a variety of linear filters such as the moving average, Butterworth, and Chebyshev type I. The PE results from simulations closely resembled our predicted results for all tested filters, which validated our theoretical propositions. More importantly, when we applied linear filters to signals with inner correlations, we were able to theoretically decouple the signal-specific contribution from that induced by the linear filter. Therefore, by providing a proper framework of PE linear filter characterization, we improved the PE interpretation by identifying possible artifact information introduced by the preprocessing steps.

scholarly journals Signal processing of C-RTD Sensor output as the input to the instrument of low temperature monitoring using Arduino Uno Rev.3

2019 ◽  
Vol 1 (2) ◽  
pp. 48
Author(s):  
Rismawan Rismawan ◽  
Moh. Toifur
Keyword(s):  
Output Signal ◽  
Low Cost ◽  
Digital Signal ◽  
Analog Signal ◽  
Digital Signals ◽  
Temperature Detector ◽  
Detector Output ◽  
Coil Resistance ◽  
Arduino Uno ◽  
Value Changes

The C-RTD (Coil-Resistance Temperature Detector) output signal is an analog signal in the form of a direct voltage. This value changes with changes in RTD temperature. This analog signal can be read by users using a multimeter or similar device but does not directly indicate the RTD temperature. In order to obtain RTD temperature values, an additional device is required. In order to have a useful value and practicality, a device that can convert analog signals into values can be read directly by the user. The microcontroller was chosen as a used device. The selected microcontroller system is Arduino Uno because has been coupled with input and output ports so users only need to enter programs related to the system being created. In the other hand Arduino Uno by considering the low cost and practical. For the measurement system, the RTD output signal must be conditioned into a digital signal using the ADC so that it can be processed by the microcontroller. From testing instrument obtained that the system has been able to convert analog RTD signals into digital signals. The range of measurement is -176°C to  0°C with an accuracy of ± 0.20 / mV. 

Sign in / Sign up

Export Citation Format

Share Document