Application Of Digital Filters Research Articles

A new design of a digital filter for an efficient field programmable gate array using quantum dot technology

Digital filtering algorithms are most frequently used to implement generic-based Field-programmable gate arrays (FPGAs) chips, which are used for higher sampling rates. In the filtering structure, delay and occupied areas play a vital role. Since the existing structures suffered from shortcomings such as high delay and high occupied area, implementing a high-performance digital filter circuit with high speed and low occupied area based on unique technology can significantly improve the performance of whole FPGA structures. One of the best technologies to implement this vital structure to solve these shortcomings is quantum-dot cellular automata (QCA) technology. This paper presents several new efficient full adders for digital filter applications based on quantum technology, including a multiplier, AND gate, and accumulator. The QCADesigner 2.0.3 tool is used to create and validate the suggested designs. According to the results, all designed circuits have simple structures with few quantum cells, low area, and low latency.

Feature-Based Bearing Fault Classification Using Taylor–Fourier Transform

This paper proposes a feature-based methodology for early bearing fault detection and classification in induction motors through current signals using the digital Taylor–Fourier transform (DTFT) and statistical methods. The DTFT allows the application of narrow bandwidth digital filters located in the spurious current signal components, wherewith it is possible to gain information to detect bearing issues and classify them using statistical methods. The methodology was implemented in MATLAB using the digital Taylor–Fourier transform for three fault types (bearing ball damage, outer-race damage, and corrosion damage) at different powering conditions: power grid source at 60 Hz and adjustable speed drive applied (60 Hz, 50 Hz, 40 Hz, 30 Hz, 20 Hz, and 10 Hz) in loading and unloading conditions. Results demonstrate a classification accuracy between 93–99% for bearing ball damage, 91–99% for outer-race damage, and 94–99% for corrosion damage.

An algorithm for the design of optimal finite wordlength FIR filters

In practical FIR digital filter applications it is often necessary to represent the filter coefficients with a finite number of bits. The finite wordlength coefficient restriction reduces the filter quality and increases the filter deviation. This increase can be reduced substantially if the optimal finite wordlength coefficients are used. Computing these coefficients is more difficult and can be slow. It was shown before that the computation time can be significantly reduced with the help of a lower bound on the deviation increase. Derivation of a new algorithm that uses a much better lower bound is the purpose of this paper. We consider the general case of a length N filter with a discrete set of allowable real coefficients and demonstrate the effectiveness of the new algorithm on a set of filter design cases. The results show that this algorithm reduces the computation times up to 3 times when compared with the previously best results.

Denoising physiological data collected during multi-band, multi-echo EPI sequences

Collecting physiological data during functional magnetic resonance imaging (fMRI) experiments can improve fMRI data cleaning and contribute to our understanding of psychophysiological processes; however, these recordings are frequently fraught with artifacts from the MRI pulse sequence. Here, we assess data from BIOPAC Systems, Inc., one of the most widely used manufacturers of physiological monitoring equipment, evaluate their recommendations for filtering such artifacts from electrocardiogram and electrodermal activity data collected during single-band, single-echo fMRI sequences, and extend these recommendations to address artifacts associated with multi-band, multi-echo fMRI sequences. While the magnitude and frequencies of artifacts differ with these aspects of pulse sequences, their effects can be mitigated via application of digital filters incorporating slice collection, multi-band factor, and repetition time. The implementation of these filters is provided both in interactive online notebooks and an open-source denoising tool.

Design and applications of adjustable 2D digital filters with elliptical and circular symmetry

Design and applications of adjustable 2D digital filters with elliptical and circular symmetry

Magnetic Signature of Gold Deposits: Example from Um Garayat Region, South Eastern Desert, Egypt

Magnetic methods of exploration have proved to be efficient and have potential in the gold mineralization industry. New magnetic processing technologies aid in improving the process of interpretation and gold opportunity identification. In this work, we show the possible application of combined digital magnetic filters to explore new gold mineralization localities with application to a well-known Au mineralization zone. Um Garayat (UG) region, southeastern desert, Egypt, is an ancient example of a potential area for gold mining. Modern analysis showed that other types of mineral concentrations are present. So, exploiting the magnetic signature of the area for future investment is of great interest. The old UG gold mine is characterized by volcanic and tectonic features such as faulting and folding that affect the arc sedimentary rock sequence of repeated deformation stages. A thorough geophysical effort has been carried out around the old gold mine in the UG area to explore the extension of mineralized ore deposits. A detailed geophysical survey using magnetics was carried out in this study together with the available aeromagnetic data. Field data sets on appropriate sites were measured, processed, and evaluated by suitable software. High magnetic anomalies were detected based on grid filter analysis and contact occurrence maps as marked as possible ore deposits after satisfying the geologic conditions for gold formation. An integrated understanding of attained results revealed that the new possible ore deposits are related directly to fault and fracture zones in the shape of lenses of variable thickness in this zone. Results show that newly detected mineral occurrences in the UG area are also controlled by major faults and hydrothermal solution enrichment along fault zones at a depth ranging from 20 to 70 m. Favorable fault/joint mineralized places were located. The relationship between the Au-quartz vein's strike direction compared with magnetic anomaly lineament analysis was studied. Search for new sources of Au and other mineral deposits in addition to quartz veins is needed as pockets of accumulated mineral-rich rock fragments are deposited in drainage wadis and fault/joint zones because of hydrothermal solution enrichment.

Identification of exon locations in DNA sequences using a fractional digital anti-notch filter

Identification of protein coding region (exon) locations in DNA sequences is a fundamental initial step in genomic signal processing (GSP). Several techniques have already been applied to achieve this challenging task. However, improvements are still needed. Transforms-based methods and digital filtering are among those techniques that have been widely used. These techniques exploit the period-3 property of protein coding regions. This paper proposes the application of a narrowband bandpass fractional digital filter to extract more selectively the single frequency component corresponding to the frequency f=1/3 from DNA sequences. The ideal fractional digital anti-notch filter has an infinite amplitude at the central frequency and two tuning parameters which may be used to independently adjust the central frequency and the amplitude frequency response. The ideal filter has been approximated and implemented efficiently as an infinite impulse response (IIR) filter. The effectiveness of the proposed method has been assessed in terms of common performance evaluation metrics computed from the results obtained using DNA sequences taken from the National Center for Biotechnology Information (NCBI) and HMR195 datasets using different numerical transformations including Voss mapping and electron–ion potential (EIIP) representation. In addition to overcome the problem of sliding window size encountered in transform-based methods, comparison with existing state-of-the-art methods for exon location identification has demonstrated superiority of the proposed method on benchmark datasets.

Comparison study of hardware architectures performance between FPGA and DSP processors for implementing digital signal processing algorithms: Application of FIR digital filter

The objective of this project is to make a detailed study on the Hardware architectures of DSP and FPGA then to carry out a comparison between the two platforms in order to achieve a better implementation while keeping to increase the performances and obtain a better signal processing quality. For this raison, we wanted to make a digital FIR filter of 40 order bandpass and a symmetrical parallel architecture of this FIR filter. Matlab's FDATOOL is used to design this filter. This tool allows us to generate the VHDL code of the filter to implement it on Altera Cyclone III FPGA which is placed on the Texas Instruments TSW6011 board, this tool also allows us to generate all the coefficients of our filter in a header file C in order to use them in a program of the FIR filter written in C which will then be loaded on the DSP TMS320C6713. This achievement allows us to distinguish between different hardware architectures and make a comparison in terms of execution speed and power consumption.

Quantitative phase imaging using a combination of flat fielding and windowed Fourier filtering demodulated by a graph cuts algorithm for screening opaque and transparent objects

In this paper, quantitative phases of opaque and transparent objects are measured precisely using a combination of flat fielding and windowed Fourier filtering demodulated by graph cuts algorithm. The modulated interferogram is corrected first by flat fielding to remove dust particles and adjust inhomogeneity of the interferogram intensity. The corrected interferogram is then convolved by windowed Fourier filtering to produce an interferogram free from speckle noise. The obtained interferogram is reconstructed by the Fourier transform method, or the wavelet method, or the angular spectrum method to extract the wrapping phase of the object. A graph cuts algorithm is used to unwrap the wrapping phase to remove the 2π ambiguity. Experimental results show that quantitative phases of the objects being screened are precisely measured by the proposed method. Moreover, the lateral resolution, which is represented by slope of the roll-off is slightly improved without applications of digital filters. Furthermore, shapes of the echinocytes of the cancerous blood cells which have the sharpest spatial features are seen clearly by the proposed method.

DeepFIR: Channel-Robust Physical-Layer Deep Learning Through Adaptive Waveform Filtering

Deep learning can be used to classify waveform characteristics ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , modulation) with accuracy levels that are hardly attainable with traditional techniques. Recent research has demonstrated that one of the most crucial challenges in wireless deep learning is to counteract the channel action, which may significantly alter the waveform features. The problem is further exacerbated by the fact that deep learning algorithms are hardly re-trainable in real time due to their sheer size. This paper proposes <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DeepFIR</i> , a framework to counteract the channel action in wireless deep learning algorithms <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">without retraining the underlying deep learning model</i> . The key intuition is that through the application of a carefully-optimized digital finite input response filter (FIR) at the transmitter’s side, we can apply tiny modifications to the waveform to strengthen its features according to the current channel conditions. We mathematically formulate the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Waveform Optimization Problem</i> <xref ref-type="disp-formula" rid="deqnWOP-deqnC1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(WOP)</xref> as the problem of finding the optimum FIR to be used on a waveform to improve the classifier’s accuracy. We also propose a data-driven methodology to train the FIRs directly with dataset inputs. We extensively evaluate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DeepFIR</i> on an experimental testbed of 20 software-defined radios, as well as on two datasets made up by 500 ADS-B devices and by 500 WiFi devices and a 24-class modulation dataset. Experimental results show that our approach (i) increases the accuracy of the radio fingerprinting models by about 35%, 50% and 58%; (ii) decreases an adversary’s accuracy by about 54% when trying to imitate other device’s fingerprints by using their filters; (iii) achieves 27% improvement over the state of the art on a 100-device dataset; (iv) increases by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\times$ </tex-math></inline-formula> the accuracy of the modulation dataset.

Removing mains interference from the mfERG by applying a post-processing digital notch filter: for the good or the bad?

PurposeIdeally, the multifocal electroretinogram (mfERG) is recorded without noticeable intrusion of mains interference. However, sometimes contamination is difficult to avoid. A post-processing digital notch filter can help to recover the retinal response even in severe cases of mains interference. While a digital filter can be designed to have little to no impact on peak times, filtering out mains interference also removes the retinal signal content of the same frequency, which may result in a change of amplitude. The present study addressed this issue in the standard first order kernel mfERG.MethodsIn 24 recordings from routine exams with no perceivable mains interference, the effects of 50-Hz and 60-Hz non-causal digital notch filters on amplitude and peak time were assessed. Furthermore, the effect of filtering on contaminated traces was demonstrated and simulated mains interference was used to provide an example of nonlinear superposition of retinal signal and mains interference.ResultsmfERG amplitudes were reduced by 0%–15% (median 6%) with the 50-Hz filter and remained virtually unaffected with the 60-Hz filter. Simulations illustrate that spurious high-frequency components can occur in the filtered signal if a strongly contaminated signal is clipped due to a limited input range of the analog-to-digital converter.ConclusionThe application of a 50-Hz digital notch filter to mfERG traces causes a mild amplitude reduction which will not normally affect the clinical interpretation of the data. The situation is even more favorable with a 60-Hz digital notch filter. Caution is necessary if the assumption of linear additivity of retinal signal and mains interference is violated.

Modified repetitive control based on comb filters for harmonics control in grid-connected applications

Power quality plays an important role in the operation of grid-connected inverters. The injected current should have a minimum harmonic content in order to comply with the local grid codes. This can be challenging due to the fact that the grid voltage can also be distorted. This paper presents the modified repetitive control method for three-phase grid-connected inverters by means of a digital comb filter application. The proposed method provides multiple harmonics compensation, simple implementation and design. It consists in complementing the Proportional-Resonant (PR) control with an appropriately tuned comb filter, which results in mitigation of the output current harmonics and reduced THD. Two types of comb filters have been proposed as a harmonic compensator, namely feedback and feedforward structures. The compensator included an additional FIR low-pass filter for increased robustness. Regardless of the structure chosen the solution is targeted at simplicity of analysis, design and implementation. Furthermore, the compensator based on the feedforward comb filter is casual, hence its implementation on the digital microprocessors is greatly facilitated. The proposed two-stage design of the control loop ensures the stability even in the case of additional poles being introduced by the feedback comb filter. Investigation on frequency variations impact is also included. The research was conducted by means of the following IT solutions: data workflow management environment, code design and generation (Matlab), and user interface design (ControlDesk). The experimental results have demonstrated the effectiveness of the proposed solution for a grid-connected converter operating in a network with distorted supply voltage.

Audio enhancement and application of digital filters for speech intelligibility in forensic digital analysis expert work (Computer Forensics)

Audio enhancement and application of digital filters for speech intelligibility in forensic digital analysis expert work (Computer Forensics)

Development of an experimental set-up to measure sound absorption coefficients of porous materials

This paper discusses the practical aspects of data acquisition and signal processing techniques involved while developing an impedance tube. Microphones, data acquisition systems, set of speakers were carefully selected, calibrated, and assembled as one unit. The raw time signal is acquired through a Virtual Instrument (VI) developed in LabVIEW, and the mathematical equations involved in the process are implemented in MATLAB R 2017a. Important considerations involved in these processes have been thoroughly discussed in the paper. The final results contained outliers that were removed by the application of digital filters. The results obtained from the application of different types of digital filters are shown, discussed, and the best combination of filters has been selected. This combination results in a robust and efficient method with an improved low-frequency response (< 250 Hz) which, in a standard commercial impedance tube, was achieved by altering the microphone spacing. The validation was performed by conducting experiments on a blank tube, melamine foam, glass wool, and comparison were made with the result obtained on the set-up of a leading manufacturer, and with the ones reported in works of literature. They show a good match between them which completes the validation.

Development of the ATLAS Liquid Argon Calorimeter Readout Electronics for the HL-LHC

Following new Trigger and Data AcQuisition (TDAQ) buffering and rate requirements as well as the high radiation doses and the pileup conditions of the High-Luminosity LHC, the ATLAS Liquid Argon Calorimeter electronics will be upgraded to readout the 182,500 calorimeter cells at 40 MHz with 16 bit dynamic range. The triangular calorimeter signals are amplified and shaped by the analogue electronics over a dynamic range of 16 bits, with low noise and excellent linearity. Developments of low-power preamplifiers and shapers to meet these requirements are ongoing in CMOS 130 nm. In order to digitize the analogue signals on two gains after shaping, radiation-hard, low-power 40 MHz 14-bit ADCs are developed using a SAR architecture in 65 nm CMOS. Characterization of the first prototypes of the Front-End components show good promise to fulfill all the requirements. The signals will be sent at 40 MHz to the off-detector electronics, that will make use of FPGAs connected through high-speed links to perform energy and time reconstruction through the application of digital filtering and appropriate corrections. Reduced data are sent with low latency to the first level trigger, while the full data are buffered until the reception of trigger accept signals. The data-processing, control and timing functions will be realized by dedicated boards connected through ATCA crates. Results of tests of the first prototypes of Front-End components will be presented, along with design studies on the performance of the off-detector readout system.

Improving Calculation Accuracy of Digital Filters Based on Finite Field Algebra

The applications of digital filters based on finite field algebra codes require their conjugation with positional computing structures. Here arises the task of algorithms and structures developed for converting the positional notation codes to finite field algebra codes. The paper proposes a method for codes conversion that possesses several advantages over existing methods. The possibilities and benefits of optimization of the computational channel structure for digital filter functioning based on the codes of finite field algebra are shown. The modified structure of computational channel is introduced. It differs from the traditional structure by the fact that there is no explicit code converter in it. The main principle is that the “reference” values of input samples, which are free from the error of the analog-digital converter, are used as input samples. The proposed approach allows achieving a higher quality of signal processing in advanced digital filters.

Application of IIR Digital Filter with A New LMS Adaptive Algorithm

Any system will be inevitably disturbed by noise. The existence of noise affects the processing and application of real signals. How to effectively suppress and eliminate noise has always been a hot spot in the industrial field. In order to design a filter which can properly adjust its parameters according to different environments to obtain the optimal value, this paper designs an adaptive IIR digital filter, and studies as well as improves the adaptive algorithm. A new variable step size LMS algorithm based on multi-scale wavelet transform is proposed in this paper. The wavelet transform domain algorithm belongs to LMS transform domain algorithm and is a new time-frequency analysis method developed, so it has the characteristics of multi-resolution analysis. This adaptive IIR filter designed is applied to suppression and cancellation of noise, and simulation experiments are performed on the MATLAB software platform, so that better illustrating the superiority of this improved algorithm.

Application of recursive digital filter (RDF) methods for baseflow separation: study at Brantas watershed

Baseflow is an important component affecting the availability of water in the river during the dry season. Availability of water in the dry season is useful for water resources management. This research aims to test and to compare six recursive digital filters (RDF) methods for calculating baseflow and baseflow index. This research was conducted in Brantas Watershed. Two outlets (sub-watersheds) located at Kertosono and Ploso were used. Daily discharge from 1996 to 2015 of the two outlets above was used as main input for this study. While rainfall data were used to determine the calibration period. The sequence procedures of this research, consist of: (1) inventory of daily discharge and rainfall data, (2) data processing, (3) calibration, (4) validation, and (5) evaluation of models’ performances. Six (6) methods of baseflow separation based on recursive digital filters were evaluated. The calibration process was carried out for periods 1996 to 2005. The periods from July to September was assumed to be the peak of the dry season and then selected for calibration process. The parameter values were calibrated using the data from dry season for each year. Furthermore, the average value of parameters obtained from calibration period then used to separate baseflow in validation process (periods 2006 to 2015). The result of separation both in calibration and validation are then evaluated using root mean square error (RMSE), coefficient of determination (R²) and FDC. This research shows that the Lyne-Hollick and EWMA filters perform better than other methods. In Brantas Kertosono sub-watershed, the optimal parameter value for Lyne Hollick algoritmh (αly) = 0.995 dan for EWMA filter (αew) = 0.003 and in Brantas Ploso sub-watershed (αly ) = 0.99 dan (αew) = 0.003.

Digital Signal Processing and Real Time Statistical Analysis in Wireless Sensor Networks Using Xbee and Java

Objective of this paper is how Digital Signal Processing can be implemented in Wireless Sensor Network (WSN) using Java. Digital Signal Processing enables the application of digital filters and algorithms. These filters have a great advantage over analog filters. Further, we have performed statistical analysis on the received dataset in real time. Statistical analysis gives us valuable information about the data and how it is distributed. The statistical analysis results will be logged in real time using the Java application.

Comparison of delayless digital filtering algorithms and their application to multi-sensor signal processing

In the phase of industry digitalization, data are collected from many sensors and signal processing techniques play a crucial role. Data preprocessing is a fundamental step in the analysis of measurements, and a first step before applying machine learning. To reduce the influence of distortions from signals, selective digital filtering is applied to minimize or remove unwanted components. Standard software and hardware digital filtering algorithms introduce a delay, which has to be compensated for to avoid destroying signal associations. The delay from filtering becomes more crucial when the analysis involves measurements from multiple sensors, therefore in this paper we provide an overview and comparison of existing digital filtering methods with an application based on real-life marine examples. In addition, the design of special-purpose filters is a complex process and for preprocessing data from many sources, the application of digital filtering in the time domain can have a high numerical cost. For this reason we describe discrete Fourier transformation digital filtering as a tool for efficient sensor data preprocessing, which does not introduce a time delay and has low numerical cost. The discrete Fourier transformation digital filtering has a simpler implementation and does not require expert-level filter design knowledge, which is beneficial for practitioners from various disciplines. Finally, we exemplify and show the application of the methods on real signals from marine systems.