Relevant bibliographies by topics / Digital filter design

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Digital filter design'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Digital filter design"

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Mewada, Hiren K., and Jitendra Chaudhari. "Low computation digital down converter using polyphase IIR filter." Circuit World 45, no. 3 (August 5, 2019): 169–78. http://dx.doi.org/10.1108/cw-02-2019-0015.

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Purpose The digital down converter (DDC) is a principal component in modern communication systems. The DDC process traditionally entails quadrature down conversion, bandwidth reducing filters and commensurate sample rate reduction. To avoid group delay, distortion linear phase FIR filters are used in the DDC. The filter performance specifications related to deep stopband attenuation, small in-band ripple and narrow transition bandwidth lead to filters with a large number of coefficients. To reduce the computational workload of the filtering process, filtering is often performed as a two-stage process, the first stage being a down sampling Hoegenauer (or cascade-integrated comb) filter and a reduced sample rate FIR filter. An alternative option is an M-Path polyphase partition of a band cantered FIR filter. Even though IIR filters offer reduced workload to implement a specific filtering task, the authors avoid using them because of their poor group delay characteristics. This paper aims to propose the design of M-path, approximately linear phase IIR filters as an alternative option to the M-path FIR filter. Design/methodology/approach Two filter designs are presented in the paper. The first approach uses linear phase IIR low pass structure to reduce the filter’s coefficient. Whereas the second approach uses multipath polyphase structure to design approximately linear phase IIR filter in DDC. Findings The authors have compared the performance and workload of the proposed polyphase structured IIR filters with state-of-the-art filter design used in DDC. The proposed design is seen to satisfy tight design specification with a significant reduction in arithmetic operations and required power consumption. Originality/value The proposed design is an alternate solution to the M-path polyphase FIR filter offering very less number of coefficients in the filter design. Proposed DDC using polyphase structured IIR filter satisfies the requirement of linear phase with the least number of computation cost in comparison with other DDC structure.
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Linville, A. Frank. "Single‐channel digital filter design for seismic applications." GEOPHYSICS 59, no. 10 (October 1994): 1584–92. http://dx.doi.org/10.1190/1.1443547.

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A general least‐squares, time‐domain filter design methodology has been developed that is easy to use for a variety of seismic filtering applications. The 1-D finite‐impulse response frequency filter can efficiently provide the noise attenuation and selectivity needed in modern data processing. Flexibility of design allows a choice of all basic types of single‐channel filters commonly used in processing. These include low‐pass, high‐pass, band‐pass, band‐reject, and notch filters. In addition, multiple bands may be passed or rejected using a single operator design without increasing the length of the filter. The ability to reject multiple noise bands with one filter is convenient and also reduces data processing costs. The filter can be viewed as a minimum‐phase Wiener‐Levinson predictive deconvolution filter designed to reject specified frequency bands. The filter is designed from an exact mathematical description of the specified stop bands that provide an explicit expression for the required autocorrelation lags in the normal equations. The filter’s desired frequency response (transition zone width and rejection level) is simply related to two input parameters—operator length and white noise level.
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Stancic, Goran, and Sasa Nikolic. "Design of narrow stopband recursive digital filter." Facta universitatis - series: Electronics and Energetics 24, no. 1 (2011): 119–30. http://dx.doi.org/10.2298/fuee1101119s.

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The procedure for design of narrow stopband recursive digital filter realized through parallel connections of two allpass sub-filters is described in this paper. This solution also allows realization of complementary filter, using only one additional adder, and exhibit low sensitivity on coefficients quantization. The method is based on phase approximation of allpass sub-filter. The procedure is very efficient and solution can be obtained within only a few iterations even for large filter order n. Every stopband provides two more equations, one at notch frequency and the other at passband boundary. It is not possible to control attenuation at both passband boundaries, but described procedure provides that achieved attenuations are less or equal to prescribed values. Using this algorithm full control of passband edges is obtained comparing with existing methods where it is not possible.
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Yue, Dachao, and Haikuan Liu. "The Design Of Intelligent Filter For EEG." MATEC Web of Conferences 232 (2018): 04023. http://dx.doi.org/10.1051/matecconf/201823204023.

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EEG data processing method is usually digital filter designed by the traditional method. Its disadvantage is the transition zone is wide and the filtering effect is poor. Using an improved particle swarm optimization algorithm on IIR digital filters design, the performances of filters designed by various methods are compared and analyzed. Experiments illustrate particle swarm optimization algorithm is effective in IIR filter design and its performance is promising.
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Karam, Lina J., and James H. McClellan. "Chebyshev digital FIR filter design." Signal Processing 76, no. 1 (July 1999): 17–36. http://dx.doi.org/10.1016/s0165-1684(98)00244-8.

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Kabalan, Karim Y., and Ali El-Hajj. "Digital filter design using spreadsheets." Computer Applications in Engineering Education 7, no. 1 (1999): 9–15. http://dx.doi.org/10.1002/(sici)1099-0542(1999)7:1<9::aid-cae2>3.0.co;2-c.

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Selesnick, I. W., and C. S. Burrus. "Generalized digital Butterworth filter design." IEEE Transactions on Signal Processing 46, no. 6 (June 1998): 1688–94. http://dx.doi.org/10.1109/78.678493.

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Wen, Hui, and Shu Ming Li. "DSP-Based FIR Filter Design and Circular Buffer Implementation." Advanced Materials Research 403-408 (November 2011): 1755–58. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.1755.

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The digital filter technology includes two aspects, which are the filter design process and filter realization. The article expounded the basic structure of FIR filter, with examples on the use Matlab to determine the FIR filter coefficient, analysis of the cycle of the buffer zone algorithm Principle, based on the algorithm, combination of filters designed to achieve the input of mixed-signal FIR digital filter. In the end, the filter is given before and after the input and output signal waveform simulation.
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Su, Te-Jen, Tsang-Chi Yang, Wen-Pin Tsai, and Jia-Wei Liu. "Design Two-Dimensional IIR Filters Based on Clonal Selection Algorithm with Singular Value Decomposition." Research Letters in Signal Processing 2007 (2007): 1–5. http://dx.doi.org/10.1155/2007/32081.

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In this letter, clonal selection algorithm (CSA) with singular value decomposition (SVD) method is investigated for the realization of two-dimentional (2D) infinite-impulse response (IIR) filters with arbitrary magnitude responses. The CSA is applied to optimize the sampled frequencies of transition band of digital filters, then producing a planar response matrix of a 2D IIR digital filter. By using the SVD, 2D magnitude specifications can be decomposed into a pair of 1D filters, and thus the problem of designing a 2D digital filter can be reduced to the one of designing a pair of 1D digital filters or even only one 1D digital filter. The stimulation results show the proposed method has the better performance of the minimum attenuation between the passband and stopband.
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Zhang, Hui, Kun Yang, Si Ming He, and Jun Li. "Design of IIR Digital Filter Based on FPGA." Applied Mechanics and Materials 427-429 (September 2013): 1968–71. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1968.

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From the request of practical applications,according to the basic theory of IIR filters, a scheme of hardware implementation is worked out combining with the fact that coefficients of numerator and denominator of transfer function are fixed and the structural feature of selected FPGA. From the clew of implementing stratified ,modularized and parameterized design ,the thesis describes the hardware implementation of the IIR filter with VHDL and schematic diagram design method.
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Dissertations / Theses on the topic "Digital filter design"

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England, Janine V. "Digital filter design techniques/." Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/23177.

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An overview and investigation of the more popular digital filter design techniques are presented, with the intent of providing the filter design engineer a complete and concise source of information. Advantages and disadvantages of the various techniques are discussed, and extensive design examples used to illustrate their application to specific design problems. Both IIR (Butterworth, Chebyshev and elliptic), and FIR (Fourier coefficient design, windows and frequency sampling) design methods are featured, as well as, the Optimum FIR Filter Design Program of Parks and McClellan, and the Minimum p - Error IIR Filter Design Method of Deczky. Keywords: Digital filter design, IIR, FIR, Butterworth, Chebyshev, Elliptic, Fourier coefficient, Windows, Frequency sampling, Remez exchange algorithm, Minimum p-error, and IRR filter design
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Kennedy, Paul B. (Paul Brodie). "Filter designer : an intuitive digital filter design environment." Thesis, McGill University, 1996. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=23849.

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The ability to accurately manipulate the spectral content of audio is indispensable for the artistic presentation of sound. While there are many devices currently available that are capable of performing this function, most tend to be either highly complex electrical engineering tools, or music-oriented products that are limited in functionality. Filter Designer was created to fill this gap by providing an environment with which musically-trained users can design and implement digital filters, while having access to control parameters and analysis data previously exclusive to the engineering field. This work explores the factors that motivated the creation of Filter Designer, and examines the process of its development, from basic user interface design to the calculation and implementation of digital filters for use with audio signals.
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Anderson, Martin S. "Design of two-dimensional PCAS digital filters and filter banks." Thesis, University of Warwick, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307968.

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Law, Ying Man. "Iterative algorithms for the constrained design of filters and filter banks /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202004%20LAW.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004.
Includes bibliographical references (leaves 108-111). Also available in electronic version. Access restricted to campus users.
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Penberthy, Harris Stephen. "Natural algorithms in digital filter design." Thesis, University of Plymouth, 2001. http://hdl.handle.net/10026.1/2752.

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Digital filters are an important part of Digital Signal Processing (DSP), which plays vital roles within the modern world, but their design is a complex task requiring a great deal of specialised knowledge. An analysis of this design process is presented, which identifies opportunities for the application of optimisation. The Genetic Algorithm (GA) and Simulated Annealing are problem-independent and increasingly popular optimisation techniques. They do not require detailed prior knowledge of the nature of a problem, and are unaffected by a discontinuous search space, unlike traditional methods such as calculus and hill-climbing. Potential applications of these techniques to the filter design process are discussed, and presented with practical results. Investigations into the design of Frequency Sampling (FS) Finite Impulse Response (FIR) filters using a hybrid GA/hill-climber proved especially successful, improving on published results. An analysis of the search space for FS filters provided useful information on the performance of the optimisation technique. The ability of the GA to trade off a filter's performance with respect to several design criteria simultaneously, without intervention by the designer, is also investigated. Methods of simplifying the design process by using this technique are presented, together with an analysis of the difficulty of the non-linear FIR filter design problem from a GA perspective. This gave an insight into the fundamental nature of the optimisation problem, and also suggested future improvements. The results gained from these investigations allowed the framework for a potential 'intelligent' filter design system to be proposed, in which embedded expert knowledge, Artificial Intelligence techniques and traditional design methods work together. This could deliver a single tool capable of designing a wide range of filters with minimal human intervention, and of proposing solutions to incomplete problems. It could also provide the basis for the development of tools for other areas of DSP system design.
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Fakhry, Nader. "Design of a Digital Compensation Filter." PDXScholar, 1995. https://pdxscholar.library.pdx.edu/open_access_etds/4961.

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The 24-bit Motorola DSP56001 processor will be used in combination with the DSP56ADC16 and the PCM-56 to design a good FIR compensation filter. Our objective is to digitize the input analog signal, and to compensate for the attenuation in the magnitude response of the digital sine wave. Two different experiments will be conducted, a hands on approach, and a simulation program. The first one will be realized directly, using the DSP system. We will determine the magnitude response of the system, and then deduce the coefficients of the FIR sin(x)/x filter. A look up table will store those values which will be fetched by the DSP program. With a minimum set of instructions we will generate a new digital output sequence after a N-point circular convolution is performed. The output signal is a good reconstruction of the input signal at frequencies below 22 Khz. However, a second experiment will be needed to improve this FIR sin(x)/x compensation filter, because we are not able to go beyond a 300-point impulse sequence. After that value (300-point), the time that each value is read and is ready to be processed by the DSP56001 becomes smaller than the time each instruction in the DSP program is executed and written to the PCM-56 via the SSI register. To be able to expand our experiment, we need to write a simulation program. A simulation program of the previous experiment, which take as input the measured magnitude response of the system. The challenge will be to find ways to map the frequency domain, by using the maximum value of each linear convolution sequence, with a finite input sequence. A step by step approach will be drawn until our final objective is reached. Our final step will be, to increase the number of sampling point in the frequency domain and will be to demonstrate that the result of the simulated program value will coincide with our objective, which is to compensate for the attenuation of the magnitude response of the system. By increasing the sampling frequency we will eventually obtain a good compensation filter.
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Lindblom, Ludvig. "Design of a Digital Octave Band Filter." Thesis, Linköpings universitet, Elektroniksystem, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-79231.

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This report describes the design and implementation of a fixed audio equalizer based on a scheme where parts of the signal spectrum are downsampled and treated differently for the purpose of reducing the computational complexity and memory requirements. The primary focus has been on finding a way of taking an equalizer based on a simple minimum-phase FIR filter and transform it to the new type of equalizer. To achieve this, a number of undesireable effects such as aliasing distortion and upsampling imaging had to be considered and dealt with. In order to achieve a good amplitude response of the system, optimization procedures were used. As part of the thesis, a cost-effective implementation of the filter has been made for an FPGA, in order to verify that the scheme is indeed usable for equalizing an audio signal.
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Dempster, Andrew. "Digital filter design for low-complexity implementation." Thesis, University of Cambridge, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362967.

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Asavathiratham, Chalee. "Digital audio filter design using frequency transformations." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/39065.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
Includes bibliographical references (leaves 80-81).
by Chalee Asavathiratham.
M.Eng.
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Tatangsurja, Hendra. "Digital filter design using stored product ROMs." Thesis, University of Ottawa (Canada), 1987. http://hdl.handle.net/10393/5332.

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Books on the topic "Digital filter design"

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S, Burrus C., ed. Digital filter design. New York: Wiley, 1987.

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England, Janine V. Digital filter design techniques. Monterey, California: Naval Postgraduate School, 1988.

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Freitas, Jolyon M. De. Digital filter design solutions. Boston, MA: Artech House, 2004.

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Steve, Winder, ed. Analog and digital filter design. 2nd ed. Amsterdam: Newnes, 2002.

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Winder, Steve. Analog and digital filter design. 2nd ed. Oxford: Newnes, 2002.

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Winder, Steve. Analog and digital filter design. 2nd ed. Amsterdam: Newnes, 2002.

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1940-, Taylor Fred J., ed. Electronic filter design handbook: LC, active, and digital filters. 2nd ed. New York: McGraw-Hill, 1988.

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Thede, Les. Practical analog and digital filter design. Boston: Artech House, 2005.

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Thede, Les. Practical analog and digital filter design. Boston: Artech House, 2004.

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Blandford, Richard K. The digital filter analyzer. Reading, Mass: Addison-Wesley, 1988.

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Book chapters on the topic "Digital filter design"

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Lynn, Paul A. "Digital Filter Design." In Digital Signals, Processors and Noise, 53–89. London: Macmillan Education UK, 1992. http://dx.doi.org/10.1007/978-1-349-22145-5_2.

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Kim, Keonwook. "Filter Design." In Conceptual Digital Signal Processing with MATLAB, 267–501. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2584-1_6.

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Berchin, Greg. "Precise Filter Design." In Streamlining Digital Signal Processing, 59–72. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118316948.ch7.

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Iyer, Shivkumar Venkatraman. "Filter Design." In Digital Filter Design using Python for Power Engineering Applications, 149–85. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61860-5_7.

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Rao, K. Deergha, and M. N. S. Swamy. "IIR Digital Filter Design." In Digital Signal Processing, 241–324. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8081-4_5.

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Rao, K. Deergha, and M. N. S. Swamy. "FIR Digital Filter Design." In Digital Signal Processing, 325–414. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8081-4_6.

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Kim, Keonwook. "Preliminary Digital Filter Design." In Conceptual Digital Signal Processing with MATLAB, 1–19. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2584-1_1.

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Jackson, Leland B. "Filter Design by Modeling." In Digital Filters and Signal Processing, 323–72. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4757-2458-5_10.

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Jackson, Leland B. "FIR Filter Design Techniques." In Digital Filters and Signal Processing, 289–321. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4757-2458-5_9.

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Jackson, Leland B. "Filter Design by Modeling." In Digital Filters and Signal Processing, 249–96. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4615-3262-0_10.

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Conference papers on the topic "Digital filter design"

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Singh Sidhu, Balraj, and J. S. Dhillon. "Higher Order Optimal Stable Digital IIR Filter Design Using Heuristic Optimization." In InSITE 2015: Informing Science + IT Education Conferences: USA. Informing Science Institute, 2015. http://dx.doi.org/10.28945/2222.

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This paper proposes the innovative methodologies for the robust and stable design of optimal stable digital infinite impulse response (IIR) filters using different mutation variants of hybrid differential evolution (HDE). A multivariable optimization is employed as the design criterion to obtain the optimal stable IIR filter that satisfies the different performance requirements like minimizing the magnitude approximation error and minimizing the ripple magnitude. HDE method is undertaken as a global search technique and exploratory search is exploited as a local search technique. The proposed different mutation variants of HDE method enhance the capability to explore and exploit the search space locally as well globally to obtain the optimal filter design parameters. The chance of starting with better solution is improved by comparing the opposite solution. Here HDE has been effectively applied for the design of higher order optimal stable band-pass, and band-stop digital IIR filters. The experimental results depict that proposed HDE methods are superior or at least comparable to other algorithms and can be efficiently applied for higher order IIR filter design.
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Sukittanon, Somsak, and Josh Potts. "Mobile digital filter design toolbox." In SOUTHEASTCON 2012. IEEE, 2012. http://dx.doi.org/10.1109/secon.2012.6197007.

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Zhou, Pang, and Dongmei Wei. "Evolutionary design of digital filter." In 2010 Sixth International Conference on Natural Computation (ICNC). IEEE, 2010. http://dx.doi.org/10.1109/icnc.2010.5583823.

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Steinbauer, Miloslav, and Radek Kubasek. "Equaripple Digital Filter Banks Design." In 2006 International Conference on Applied Electronics. IEEE, 2006. http://dx.doi.org/10.1109/ae.2006.4382993.

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He, Ping, HongLi Chang, Han Gao, and ZiYi Wang. "Design of IIR digital filter." In 2017 6th International Conference on Computer Science and Network Technology (ICCSNT). IEEE, 2017. http://dx.doi.org/10.1109/iccsnt.2017.8343749.

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Economou, D., C. Mavroidis, and I. Antoniadis. "Comparison of Robust Residual Vibration Suppression Capabilities of Conventional Digital Filters." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/vib-21472.

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Abstract Digital filters consist a quite effective robust residual vibration tool, when they are used for preconditioning any excitation function, prior to its application in a flexible system. Since a quite large number of conventional digital filters already exist, each one obtained by a different design procedure and resulting to different characteristics, a systematic comparison of their capabilities is performed. Critical design parameters are addressed, influencing the filter behavior in vibration suppression, such as the total delay introduced by the filter, the permitted residual vibration error, the robustness degree achieved and the necessary computational requirements in their implementation. It is shown, that although mere does not exist a single type of filter, simultaneously conforming to an optimal degree to all the design requirements, a large variety of conventional filters can be effectively used for the several individual residual vibration suppression requirements.
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Wang, Junwei, Liangchao Ren, Peiying Yang, and Nan Gao. "Frequency sampling based FIR digital filter design." In 2006 7th International Conference on Computer-Aided Industrial Design and Conceptual Design. IEEE, 2006. http://dx.doi.org/10.1109/caidcd.2006.329318.

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Wu, Huicong, and Xuejun Song. "Digital Filter Design Using Evolutionary Algorithms." In 2010 2nd International Workshop on Intelligent Systems and Applications (ISA). IEEE, 2010. http://dx.doi.org/10.1109/iwisa.2010.5473272.

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Weiss, S., M. Harteneck, and R. W. Stewart. "On implementation and design of filter banks for subband adaptive systems." In IEE Colloquium on Digital Filters: An Enabling Technology. IEE, 1998. http://dx.doi.org/10.1049/ic:19980295.

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Lesnikov, V., T. Naumovich, and A. Chastikov. "Generation and decomposition of digital filter topology." In 2017 IEEE East-West Design & Test Symposium (EWDTS). IEEE, 2017. http://dx.doi.org/10.1109/ewdts.2017.8110161.

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Reports on the topic "Digital filter design"

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Fakhry, Nader. Design of a Digital Compensation Filter. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.6837.

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Bolen, Scott M. Digital Filter Designs that are Free of Limit Cycles. Fort Belvoir, VA: Defense Technical Information Center, June 1994. http://dx.doi.org/10.21236/ada282885.

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Slattery, Kevin. Unsettled Topics on the Benefit of Additive Manufacturing for Production at the Point of Use in the Mobility Industry. SAE International, February 2021. http://dx.doi.org/10.4271/epr2021006.

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An oft-cited benefit of additive manufacturing (AM), or “3D-printing,” technology is the ability to produce parts at the point of use by downloading a digital file and making the part at a local printer. This has the potential to greatly compress supply chains, lead times, inventories, and design iterations for custom parts. As a result of this, both manufacturing and logistics companies are investigating and investing in AM capacity for production at the point of use. However, it can be imagined that the feasibility and benefits are a function of size, materials, build time, manufacturing complexity, cost, and competing technologies. Because of this, there are instances where the viability of point-of-use manufacturing ranges from the perfect solution to the worst possible choice. Unsettled Topics on the Benefits of Additive Manufacturing for Production at the Point of Use in the Mobility Industry discusses the benefits, challenges, trade-offs, and other determining factors regarding this new level of AM possibilities.
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