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Filter Design Solutions for RF systems
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A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section " Circuit and Signal Processing ".
Deadline for manuscript submissions: closed (31 May 2020) | Viewed by 48016
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Dear Colleagues,
This Special Issue will focus on the state-of-the-art results in the definition and design of filters for low- and high-frequency applications and systems. Different technologies and solutions are commonly adopted for filter definition, from electrical to electromechanical and mechanical solutions, from passive to active devices, and from hybrid to integrated designs. Aspects related to both theoretical and experimental research in filter design; CAD modeling; novel technologies and applications; and filter fabrication, characterization, and testing will be covered. Potential authors are invited to submit original research articles and review papers on the following topics:
- The modelling, design, and simulation of filters;
- Processes and fabrication technologies for filters;
- The automated characterization and testing of filters;
- Voltage and current-mode filters;
- Integrated and discrete filters;
- Passive and active filters;
- Variable filters, characterization, and tunability.
Prof. Dr. Leonardo Pantoli Prof. Dr. Vincenzo Stornelli Guest Editors
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- Filter design
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Published Papers (11 papers)
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- Corpus ID: 41854223
IIR Digital Filter Design Research and Simulation on MATLAB
- Chengliang Zhang , Aihong Wang
- Computer Science, Engineering
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10 Citations
Iir based digital filter design and performance analysis.
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Design of Biquad Filter in Digital Hearing Aid
Design of costas loop for carrier recovery mechanism of bpsk demodulation, transmission of audio signal through different filters to reduce awgn from channel and recode there digital response, a low-area based costas loop implementation for bpsk signals, design and application of silicon on insulator based sige vtfet in iir filter by balanced truncation (bt) method of model order reduction, a hybrid approach for extracting emg signals by filtering eeg data for iot applications for immobile persons, different methods for acquisition and analysis of ecg signal using biomedical software, theoretical and applied, distribution analysis of functional daily tasks with the kinect device, 8 references, a square-root nyquist (m) filter design for digital communication systems, a complexity reduction approach for fir notch filter design, iir digital filtering of non-uniformly sampled signals via state representation, design of low-pass filters using defected ground structure, iir approximation of fir filters via discrete-time vector fitting, optimized fir filter design based on self-adaptive genetic algorithm, dsp system design: complexity reduced iir filter implementation for practical applications, related papers.
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Design of a series-coupled microring resonator wavelength filter using the digital filter design method
Iir based digital filter design for denoising the photoplethysmography signal, a survey of optimal polynomial approximants, applications to digital filter design, and related open problems, development of a low-cost and effisient ecg devices with iir digital filter design.
Measurement of biosignals such as electrocardiograph has the interpretation of noise from other signals. The noise can interfere with the measurement of the heart signal and make the measurement inaccurate, so the purpose of this study is to make a 6-Lead Electrocardiogram module with an Arduino-Based Digital Filter. By using a digital filter. The contribution of this research is the use of digital filters to eliminate noise in electrocardiograph signals. This research uses Infinite Impulse Filter digital filters such as Butterworth, Chebyshev I, Chebyshev II, and Elliptic in order 2, 4, 6, 8, and 10. The study was conducted by providing input from the Function Generator on Arduino which has been applied digital filters with Frequency with 0.5Hz – 100Hz cut-off. The instrument is compared with a factory electrocardiograph. Filter measurements using 460 input data. Butterworth filter with the greatest emphasis on order 8 frequency 0.5Hz produces an emphasis of -5.74298158 dB and a frequency of 100Hz produces an emphasis of -5.93529424 dB. The Chebyshev I filter has the greatest emphasis on order 6 frequency 0.5Hz producing an emphasis of -3.27104076 dB and on order 8 frequency 100Hz producing an emphasis of -5.08730424 dB. Chebyshev II filter the biggest emphasis on the order of frequency 0.5Hz produces a suppression of -44,66011104 dB and 80Hz frequency produces a suppression of -37,3653957 dB. Elliptic filters the greatest emphasis on order 6 frequency 0.5Hz produces an emphasis on -1.55429354 dB and 100Hz frequency on order 8 produces an emphasis on -2.2849115 dB. The results showed that what was appropriate with the cut-off frequency was the Butterworth order 8 filter which was suitable for the application of the Electrocardiograph signal filter because it had bandwidth that suppressed the signal outside the cut-off frequency. The results of this study can be implemented on a 6-Lead ECG module to eliminate noise or interference when tapping ECG signals.
An Optimal Digital Filtering Technique for Incremental Delta-Sigma ADCs Using Passive Integrators
This paper presents an optimal digital filtering technique to enhance the resolution of incremental delta-sigma modulators (incremental DSMs, IDSMs) using a low-power passive integrator. We first describe a link between a passive integrator and its impact on the output of the IDSM. We then show that the optimal digital filter design can be cast as a convex optimization problem, which can be efficiently solved. As a test vehicle of the proposed technique, we use a behavioral 2nd-order IDSM model that captures critical non-idealities of the integrator, such as gain compression and output saturation. The effectiveness of the presented technique is verified using extensive simulations. The result shows that the presented filtering technique improves signal-to-noise and distortion ratio (SNDR) by 15 dB–20 dB, achieving SNDR over 90 dB when the oversampling ratio (OSR) = 256, and this corresponds to best-in-class performance when compared to previously published DSM designs using passive integrators.
Digital Filter Design Based on ARDUINO and Its Applications
Preliminary digital filter design, optimum digital filter design for removal of different noises from biomedical signals, teaching digital filter design techniques used in high fidelity audio, digital filter design for classifying coconut ages using blackman fir and elliptic iir filters, export citation format, share document.
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Why use a filter for the study methodology? Why not?
Search filters by study design.
- Non-randomized/Observational Designs
Don't Limit if You Don't Have To
It's tempting to use a methodology filter to eliminate undesirable study designs because it seems like an easy way to reduce the size of large retrieval sets, but it's alway preferable not to limit by the type of study . In most cases, such limits will result in the exclusion of relevent studies because of the large variety of terms used to describe study types. Moreover, indexing in the major databases for study types has only recently been a priority, limiting the effectiveness of controlled vocabulary in culling retrieval sets. For non-randomized designs the problem is especially severe since many authors never mention methodologies in either the title or abstract, and indexing is inconsistent. Fortunately, in many cases, an effective search involving a patient population, and intervention and an outcome will produce a managable set of results that requires no methodology filter. Define the scope of your study with this in mind.
But if You Have to Limit ...
Sometimes retrieval sets are truly unmanagable and you'll need or want to employ a methodology filter. Attempts have been made to validate many different filters. The most successful are for randomized controlled trials. These are effective because authors frequently identify their randomization methods in the title or abstract, and since the mid-1990s, controlled vocabulary has been applied in regular ways in both MEDLINE and Embase. Validated filters, which have been tested against gold-standard sets of bibliographic records, are available for other types of designs. If at all possible use one of these validated filters. You'll get decent results and will have a way of justifying your choice to the reviewers and readers of your paper. See the subtabs to this page for information on specific design classes.
More Search Filters
- CADTH Search Filters Database https://searchfilters.cadth.ca/
- Hedges Project, Health Information Research Unit, MacMaster University. http://hiru.mcmaster.ca/hiru/HIRU_Hedges_home.aspx
- InterTASC Search Filter Resource, Centre for Reviews and Dissemination http://www.york.ac.uk/inst/crd/intertasc/
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IMAGES
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Explore the latest full-text research PDFs, articles, conference papers, preprints and more on FILTER DESIGN. Find methods information, sources, references or conduct a literature review on FILTER ...
Abstract: In signal processing, a finite impulse response (FIR) filter settles to zero in finite time. FIR filters can be discrete-time or. continuous-time, and digital or analog. FIR filter is ...
FIR filters are more preferred over the IIR filter because of its stability, linear phase characteristics. In order to meet the desired precise frequency specifications, higher order filter is necessary. ... This paper presents the design of FIR filter using Hamming window, Kaiser Window and equiripple techniques. And also, a 2D FIR filter is ...
This paper presents a novel design methodology for an optimized FIR digital filters from software level to the hardware level. The main goal is to encompass all the fields that are used in the efficient hardware realization of filters i.e. design method, selection of structure and the algorithm to reduce the arithmetic complexity of FIR filtering.
Digital filters are mandatory for digital signal processing. This paper presents digital filter dispelling the unwanted signals or noise from the required signal and enhances the better performances of the signal. The extracted features of the digital filter have been analyzed to acquire the better output of the signal by using IIR Butterworth filter. It provides different designed parameters ...
Aspects related to both theoretical and experimental research in filter design; CAD modeling; novel technologies and applications; and filter fabrication, characterization, and testing will be covered. ... This paper describes the design and the development of the different components of the teslameter. Performance results are presented that ...
Analog Filters are used in a host of applications and are key building blocks in a number of applications. The main components in active filters are Op Amp (VCVS) or Transconductance Amplifier (VCCS), resistors and capacitors. In this presentation we discuss different implementations of non-conventional Amplifiers and their strengths and weakness. Also we present different non-conventional ...
An IIR filter overview. Digital IIR filter is characterized by linear difference equation defined as [8]: (1) y k + ∑ n = 1 N b n · y k - n = ∑ n = 0 M a n · x k - n where, y ( k) is the response sequence, when excited by the input sequence of x ( n ), an and bn are the associated coefficients.
This paper presents a new design of a effective IIR filter, which realized via two methods. MATLAB is a popular numerical analysis software, providing a wealth of design tool. A MATLAB-based digital filter design procedure designs the filter, and mainly analyzes the 5-order IIR filter, which is designed using Simulink.
Parks-McClellan's design procedure is generally used as a benchmark against which to compare newly proposed design methods, because it affords the best results obtained so far for real coefficients FIR filters . On the other hand, Kaiser's design approach is generally considered the most satisfactory among the known window-based ones.
New technologies for designing filter are being research all over the world to meet the growing demand for advance filter design with greater frequencies response and characteristic. Filter design often grapple with the trade-off among electrical and physical parameters such as physical size, insertion loss, loss variation, isolation, group
While in India, he worked as an electronics engineer (1968-1972) at the Indian Space Research Organization, and as a lecturer (1972-1978) in the Indian Institute of Technology. From 1983 to 1991, he worked as a senior radio-frequency electronic circuit and senior radio-frequency integrated circuit design engineer in various organizations in Canada.
Explore the latest full-text research PDFs, articles, conference papers, preprints and more on FILTER DESIGN. Find methods information, sources, references or conduct a literature review on FILTER ...
The work reported in this paper deal with of Finite Impulse Response FIR digital filter design by using window method. The window method is easiest to design FIR, but lacks flexibility especially when the passband and stopband ripples are different. The digital filter is used to filter discrete time signals with the ability to modify the frequency response of the filter at any time and it used ...
This research paper describes digital FIR low pass filter design using two variants of PSO- Attractive and Repulsive PSO (ARPSO) and Craziness based PSO (CRPSO). FIR low pass filter design with conventional approaches involve a large no of coefficients if no phase distortion or sharp cutoff in output signal is mandatory.
detection [7] and deep packet inspection [4]. The survey paper [1] contains other recent work and useful references. In addition to their simplicity, this rather wide applicability have made Bloom filters very interesting objects of study. Two exciting fronts are open in Bloom filter research: (i) innovations to the basic design, and
The contribution of this research is the use of digital filters to eliminate noise in electrocardiograph signals. This research uses Infinite Impulse Filter digital filters such as Butterworth, Chebyshev I, Chebyshev II, and Elliptic in order 2, 4, 6, 8, and 10. The study was conducted by providing input from the Function Generator on Arduino ...
A t ypical filter design process involves. selecting (1) a filter geometry that c onforms to the core geometry and addresses the site specific foundation conditions and (2) finding a suitable filt ...
Results show that, for the optimum values of the filter orders, in comparison with the FIR filter, the IIR filter attenuates the noise better (2,25 vs 84,35 x10-6 V-2), with a faster response (10.43 vs 202.05 ms), but with a greater distortion in the passband of the filter (234,76 vs 134,63 x10-6 V-2).
Abstract: This article presents, in a simplified manner, a design method for active filters intended for those who are not filter specialists. By following the described five-step approach, a circuit designer who has some knowledge of passive filters will (without having to learn a whole new technology) be able to design active filters just as easily as he now handles conventional passive filters.
bandwidth (6 dB points). The document covers fundamental of various type of filters, detail Chatterjee, S Page 5 design of MTM-ZOR based band pass filter and its compression with the conventional microstrip filters. The design is done using ADS-2012 software which work on Method of moments. Rogers RT droid board RT 6010 is used for this design.
A common DSP task is to design a frequency-selective lter to approximate either a desired impulse response or desired frequency response within certain tolerances. In some cases, the maximum passband gain may be 1. In some cases, the magnitude axis may be in decibels. Most of the design techniques are speci c to the design of lowpass lters.
You'll get decent results and will have a way of justifying your choice to the reviewers and readers of your paper. See the subtabs to this page for information on specific design classes. More Search Filters. CADTH Search Filters Database https://searchfilters.cadth.ca/ Hedges Project, Health Information Research Unit, MacMaster University.