Comments on "On the approximation problem for recursive digital filters with arbitrary attenuation curve in the pass-band and the stop-band"

Non-iterative analytic techniques are presented which employ orthogonal polynomials in the design of linear phase non-recursive digital/filters. Pass band and stop band transformations are desired to approximate an ideal low pass digital filter. Also the economization of power series technique is employed to derive near optimum responses.

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A NEW METHOD FOR DESIGN OF SELECTIVE DIGITAL IIR FILTERS WITH ARBITRARY PHASE

Facta Universitatis Series Automatic Control and Robotics ◽

10.22190/fuacr1803191d ◽

2019 ◽

Vol 17 (3) ◽

pp. 191

Author(s):

Miloš Đurić ◽

Goran Stančić ◽

Miloš Živković

Keyword(s):

Arbitrary Shape ◽

Digital Filters ◽

Piecewise Linear ◽

Stop Band ◽

New Method ◽

Pass Band ◽

Parallel Connection ◽

Iir Filters ◽

Quadratic Phase ◽

Arbitrary Phase

In this paper the design of selective digital filters that consists of parallel connection of two all-pass sub-filters is presented. The phase of this filters has given arbitrary shape ϕ(ω) in both pass-band and stop-band. The proposed method allows the calculation of selective filters with elliptic-like magnitude characteristic. Equations given in the paper are general and suitable for design of filters with arbitrary phase. The efficiency of the method is demonstrated on design of filters with piecewise linear and quadratic phase.

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On a Design of Narrowband FIR Low-Pass Filters

Encyclopedia of Information Science and Technology, Second Edition ◽

10.4018/978-1-60566-026-4.ch460 ◽

2011 ◽

pp. 2882-2887

Author(s):

Gordana Jovanovic Dolecek ◽

Javier Diaz Carmona

Keyword(s):

Impulse Response ◽

High Frequency ◽

Digital Filters ◽

Stop Band ◽

Low Frequency ◽

Pass Band ◽

Low Pass ◽

Frequency Components ◽

Band Pass ◽

High Pass

Stearns and David (1996) states that “for many diverse applications, information is now most conveniently recorded, transmitted, and stored in digital form, and as a result, digital signal processing (DSP) has become an exceptionally important modern tool.” Typical operation in DSP is digital filtering. Frequency selective digital filter is used to pass desired frequency components in a signal without distortion and to attenuate other frequency components (Smith, 2002; White, 2000). The pass-band is defined as the frequency range allowed to pass through the filter. The frequency band that lies within the filter stop-band is blocked by the filter and therefore eliminated from the output signal. The range of frequencies between the pass-band and the stop-band is called the transition band and for this region no filter specification is given. Digital filters can be characterized either in terms of the frequency response or the impulse response (Diniz, da Silva & Netto, 2002). Depending on its frequency characteristic, a digital filter is either low-pass, high-pass, band-pass, or band-stop filters. A low-pass (LP) filter passes low frequency components to the output, while eliminating high-frequency components. Conversely, the high-pass (HP) filter passes all high-frequency components and rejects all low-frequency components. The band-pass (BP) filter blocks both low- and high-frequency components while passing the intermediate range. The band-stop (BS) filter eliminates the intermediate band of frequencies while passing both low- and high-frequency components. In terms of their impulse responses digital filters are either infinite impulse response (IIR) or finite impulse response (FIR) digital filters. Each of four types of filters (LP, HP, BP, and BS) can be designed as an FIR or an IIR filter (Ifeachor & Jervis, 2001; Mitra, 2005; Oppenheim & Schafer, 1999).

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Advanced Digital Signal Processing Techniques on the Classification of the Heart Sound Signals

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2020.3127 ◽

2020 ◽

Vol 10 (9) ◽

pp. 2010-2015

Author(s):

Meisu Zhong ◽

Yongsheng Yang ◽

Yamin Zhou ◽

M. Octavian Postolache ◽

M. Chandrasekar ◽

...

Keyword(s):

Signal Processing ◽

Digital Signal Processing ◽

Impulse Response ◽

Digital Filters ◽

Heart Sound ◽

Digital Signal ◽

Pass Band ◽

Entire Study ◽

Zero Crossing ◽

Recursive Digital Filters

Speech processing subject primarily depends on the digital signal processing (DSP) methods, such as convolution, discrete Fourier transform (DFT), fast Fourier transforms (FFT), finite impulse response (FIR) and infinite impulse response (IIR) filters, FFT recursive and non-recursive digital filters, FFT processing, random signal theory, adaptive filters, upsampling and downsampling, etc. Recursive and non-recursive digital filters are primarily deployed to absorb the signal of interest signals and to block the unwanted signals (noise). Broadly, low-pass, high-pass, band-pass, and band-stop filters are implemented for filtering functions. In frequent, the DSP theories can be used for further biomedical engineering domains like biomedical imaging (MRI, ultrasound, CT, X-ray, PET) and genetic signal analysis-cum-processing too. In this article, the experiments such as voiced/unvoiced detection, formants estimation using FFT and spectrograms, pitch estimation and tracking and yes/no sound classification are used. Also, the analysis of normal/abnormal heart sound signals using simple energy computation and the zero-crossing rate and their results are obtained. For the entire study, the Matlab R2018a tool is used to obtain the simulation results. At last, the criticism, feedbacks, comments, reactions from the student are detailed for the exceptional development of the course.

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