scholarly journals A Mathematical Review of Polyphase Filterbank Implementations for Radio Astronomy

2011 ◽  
Vol 28 (4) ◽  
pp. 317-322 ◽  
Author(s):  
Christopher Harris ◽  
Karen Haines
Keyword(s):  
Signal Processing ◽  
Radio Astronomy ◽  
Advantages And Disadvantages ◽  
Mathematical Background ◽  
Mathematical Review ◽  
Hardware Architectures ◽  
Published Research ◽  
General Scope

AbstractThe technique of polyphase filterbanks is commonly used for signal processing in radio astronomy. The rapid and ongoing evolution of parallel hardware architectures requires optimised implementations of such techniques to be redeveloped. However, much of the published research regarding polyphase filterbanks refers the reader to signal processing books with a more general scope. Furthermore, these references tend to focus on the design of filters, rather than their implementation. For this reason, this work presents a mathematical background for the implementation of a polyphase filterbank specific to radio astronomy. It also addresses the advantages and disadvantages of polyphase filterbanks in comparison with more commonly used techniques.

Epileptic Seizure Prediction Using Deep Transformer Model

2021 ◽  
Author(s):  
Abhijeet Bhattacharya ◽  
Tanmay Baweja ◽  
S. P. K. Karri
Keyword(s):  
Signal Processing ◽  
Deep Learning ◽  
False Positive Rate ◽  
Superior Performance ◽  
Seizure Prediction ◽  
Advantages And Disadvantages ◽  
Positive Rate ◽  
Benchmark Datasets ◽  
Automated Screening ◽  
Transformer Model

The electroencephalogram (EEG) is the most promising and efficient technique to study epilepsy and record all the electrical activity going in our brain. Automated screening of epilepsy through data-driven algorithms reduces the manual workload of doctors to diagnose epilepsy. New algorithms are biased either towards signal processing or deep learning, which holds subjective advantages and disadvantages. The proposed pipeline is an end-to-end automated seizure prediction framework with a Fourier transform feature extraction and deep learning-based transformer model, a blend of signal processing and deep learning — this imbibes the potential features to automatically identify the attentive regions in EEG signals for effective screening. The proposed pipeline has demonstrated superior performance on the benchmark dataset with average sensitivity and false-positive rate per hour (FPR/h) as 98.46%, 94.83% and 0.12439, 0, respectively. The proposed work shows great results on the benchmark datasets and a big potential for clinics as a support system with medical experts monitoring the patients.

Digital Watermarking Techniques for Audio and Speech Signals

2011 ◽  
pp. 132-160
Author(s):  
Aparna Gurijala ◽  
John R. Deller Jr.
Keyword(s):  
Signal Processing ◽  
Performance Evaluation ◽  
Digital Watermarking ◽  
State Of The Art ◽  
Audio Watermarking ◽  
Speech Signals ◽  
Advantages And Disadvantages ◽  
Signal Features

The main objective of this chapter is to provide an overview of existing speech and audio watermarking technology and to demonstrate the importance of signal processing for the design and evaluation of watermarking algorithms. This chapter describes the factors to be considered while designing speech and audio watermarking algorithms, including the choice of the domain and signal features for watermarking, watermarked signal fidelity, watermark robustness, data payload, security, and watermarking applications. The chapter presents several state-of-the-art speech and audio watermarking algorithms and discusses their advantages and disadvantages. The various applications of watermarking and developments in performance evaluation of watermarking algorithms are also described.

Improving the Performance and Resource Utilization of the CASPER FFT and Polyphase Filterbank

2016 ◽  
Vol 05 (04) ◽  
pp. 1641002
Author(s):  
Ryan Monroe
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Resource Utilization ◽  
Radio Astronomy ◽  
Digital Signal ◽  
Quantization Noise

The effectiveness of Digital Signal Processing (DSP) solutions for radio-astronomy is limited by the efficiency of the implemented algorithms. Novel implementations of several popular DSP algorithms are presented. Their optimization strategies are discussed and their efficiency is compared to that of the standard Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) library solutions. Compared to CASPER, the PFB-FIR and FFT modules require 73% and 45% of the DSP48E1 resources, with performance dominated by ADC quantization noise for typical radio-astronomy inputs.

scholarly journals Square Kilometre Array Station Configuration Using Two-Stage Beamforming

2013 ◽  
Vol 30 ◽  
Author(s):  
Aziz Jiwani ◽  
Tim Colegate ◽  
Nima Razavi-Ghods ◽  
Peter J. Hall ◽  
Shantanu Padhi ◽  
...  
Keyword(s):  
Signal Processing ◽  
Radio Astronomy ◽  
Effective Area ◽  
The Other ◽  
Processing Load ◽  
Two Stage ◽  
Square Kilometre Array ◽  
Cost Benefits ◽  
Sparse Aperture ◽  
Aperture Arrays

AbstractThe lowest frequency band (70–450 MHz) of the Square Kilometre Array (SKA) will consist of sparse aperture arrays grouped into geographically localised patches or stations. Signals from thousands of antennas in each station will be beamformed to produce station beams which form the inputs for the central correlator. Two-stage beamforming within stations can reduce SKA-low signal processing load and costs, but has not been previously explored for the irregular station layouts now favoured in radio astronomy arrays. This paper illustrates the effects of two-stage beamforming on sidelobes and effective area, for two representative station layouts (regular and irregular gridded tiles on an irregular station). The performance is compared with a single-stage, irregular station. The inner sidelobe levels do not change significantly between layouts, but the more distant sidelobes are affected by the tile layouts; regular tile creates diffuse, but regular, grating lobes. With very sparse arrays, the station effective area is similar between layouts. At lower frequencies, the regular tile significantly reduces effective area, hence sensitivity. The effective area is highest for a two-stage irregular station, but it requires a larger station extent than the other two layouts. Although there are cost benefits for stations with two-stage beamforming, we conclude that more accurate station modelling and SKA-low configuration specifications are required before design finalisation.

Comparative characteristics of anti-collision processing of radio signal from identification tags on surface acoustic waves

2019 ◽  
pp. 48-56 ◽  
Author(s):  
A. V. Sorokin ◽  
A. P. Shepeta ◽  
V. A. Nenashev ◽  
G. M. Wattimena
Keyword(s):  
Signal Processing ◽  
Surface Acoustic Waves ◽  
Group Identification ◽  
Sensor Data ◽  
Correct Identification ◽  
Processing Methods ◽  
Time Frequency ◽  
Advantages And Disadvantages ◽  
Identification Tags ◽  
Signal Processing Methods

Introduction:Collision of information signals is a common problem in the measurement of physical magnitudes, such as temperature, pressure, stress, etc., with acoustic-electronic sensors. This problem is caused by overlapping response signals in the time domain, which makes it difficult to interpret correctly the device identification codes or the sensor data received.Purpose:Analysis of anticollision algorithms for radio-frequency tag code detection and identification by response information signals from acoustic-electronic devices which use the methods of time, frequency and frequency-time division of the response radio signals.Methods:Probabilistic methods for calculating the parameters of digital detectors of radio pulse bursts with given false alarm values and gaussian white noise background; individual code group identification methods when studying the attenuation of acoustic-electric signal during their propagation in the tag substrate, taking into account the dependence of the attenuation on the tag topology.Results:We have derived analytical expressions to calculate the probability of the correct identification of each tag, taking into account the dependence on tag topology, attenuation characteristics, the anti-collision signal processing methods and the signal-to-noise ratios. Curves which allow you to compare the advantages and disadvantages of the considered anti-collision signal processing methods are calculated and shown in the article. The analysis of the graphic charts demonstrating the correct identification probability has shown that identification tags with frequency-time coding have better ratios as compared to frequency or time methods of collision prevention.Practical relevance:The obtained result allows you to effectively evaluate the condition of technical objects, improving the predictability and prevention of possible environmental and man-made disasters.

COMBINED SIGNAL PROCESSING METHOD FOR DIAGNOSIS AND MONITORING OF THE INDUCTION MOTORS OPTIMIZED FOR EMBEDDED SYSTEMS

2021 ◽  
pp. 18-27
Author(s):  
A. L. Morozov
Keyword(s):  
Signal Processing ◽  
Embedded Systems ◽  
Induction Motors ◽  
Vibration Signal ◽  
Constant Load ◽  
Load Level ◽  
Monitoring Systems ◽  
Vibration Signals ◽  
Advantages And Disadvantages ◽  
Fractional Moments

Induction Motors (IM) play a key role in modern industry, so the condition monitoring systems are becoming increasingly relevant. Commercial monitoring systems are usually based on the measurement of IM’s vibrations and the further processing of the measured vibration signals. For those purposes the embedded systems (such as microcontrollers and inexpensive processors) are used. Embedded systems have limited resources, so data processing algorithms should have low computational complexity and require little memory. In this paper, the wellknown methods of processing vibration signals for fault diagnosis of the IM are considered and their main advantages and disadvantages for the implementation in embedded systems are highlighted. The previously proposed method based on a combination of the fast Fourier transform and the statistics of the fractional moments is optimized for vibration signal processing and implementation in embedded systems. The efficiency of diagnosis of such faults as eccentricity and a broke rotor bar, using the proposed method, is verified on the radial vertical vibrations measurements of the real motors under different constant load levels: no load, 50 % of the rated load, 75% of the rated load. The results show that this approach allows accurately diagnose the considered faults independently from the load level.

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