Theory of the Design, and Operation of Digital Filters

Bilinear Transformation ◽

Finite Impulse Response Filters ◽

Infinite Impulse Response Filters ◽

Basic Characteristics ◽

Chapter 16 present the theoretical basis for digital filters, including issues related to their design. The basic characteristics and structures of finite impulse response and infinite impulse response filters are presented and discussed. In addition, the ideal and practical transfer characteristics of the digital filters are defined. The basic advantage of finite impulse response filters is that they can be designed to have an exact linear phase. However, infinite impulse response filters are generally more efficient computationally. The methods for filters design and related algorithms, which are based on the bilinear transformation method, windowed Fourier series, and algorithms based on iterative optimization, are also presented.

Application of Digital Filters to Check Quality of the Automatically Scaled Ionograms

Journal of Electrical Engineering ◽

10.2478/jee-2015-0026 ◽

2015 ◽

Vol 66 (3) ◽

pp. 164-168 ◽

Cited By ~ 5

Author(s):

Luboš Rejfek ◽

Zbyšek Mošna ◽

Daniel Kouba ◽

Josef Boška ◽

Dalia Burešová

Keyword(s):

Impulse Response ◽

Digital Filters ◽

Finite Impulse Response ◽

The State ◽

Simple Method ◽

Automatic Scaling ◽

Finite Impulse Response Filters ◽

Basic Characteristics ◽

Abstract The ionospheric observatory Pruhonice serves to monitor the state of ionosphere using ground-based vertical sounding instrument - the Digisonde DPS-4D. Measured ionograms are automatically evaluated (scaled) and basic characteristics are derived. The ionograms and the scaled parameters are sent to the international databases. Especially during disturbed conditions the automatic scaling could give unreliable results. This paper presents simple method how to detect accidental errors in automatic scaling based on the parameters derived from ionograms and on an application of the finite impulse response filters.

Real-Time Digital Filters: Infinite Impulse Response Filters

Analytical Chemistry ◽

10.1021/ac00157a731 ◽

1988 ◽

Vol 60 (6) ◽

pp. 403A-413A ◽

Cited By ~ 20

Author(s):

Stephen E. Bialkowski

Keyword(s):

Real Time ◽

Impulse Response ◽

Digital Filters ◽

Infinite Impulse Response Filters ◽

Transformations for FIR and IIR Filters’ Design

Symmetry ◽

10.3390/sym13040533 ◽

2021 ◽

Vol 13 (4) ◽

pp. 533

Author(s):

V. N. Stavrou ◽

I. G. Tsoulos ◽

Nikos E. Mastorakis

Keyword(s):

Impulse Response ◽

Transfer Functions ◽

Finite Impulse Response ◽

Transformation Method ◽

Optimization Techniques ◽

Two Dimensional ◽

Bilinear Transformation ◽

One Dimensional ◽

Iir Filters

In this paper, the transfer functions related to one-dimensional (1-D) and two-dimensional (2-D) filters have been theoretically and numerically investigated. The finite impulse response (FIR), as well as the infinite impulse response (IIR) are the main 2-D filters which have been investigated. More specifically, methods like the Windows method, the bilinear transformation method, the design of 2-D filters from appropriate 1-D functions and the design of 2-D filters using optimization techniques have been presented.

ECG Signal Denoising with Field-Programmable Gate Array Implementation of Fast Digital Finite Impulse Response and Infinite Impulse Response Filters

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2020.2842 ◽

2020 ◽

Vol 10 (1) ◽

pp. 81-85

Author(s):

R. Mohanraj ◽

R. Vimala

Keyword(s):

Impulse Response ◽

Field Programmable Gate Array ◽

Finite Impulse Response ◽

Signal Denoising ◽

Ecg Signal ◽

Infinite Impulse Response Filters ◽

Field Programmable ◽

Gate Array ◽

Multi-Rate Discrete-Time Signal Processing

10.1093/oso/9780198860792.003.0017 ◽

2021 ◽

pp. 824-852

Author(s):

Stevan Berber

Keyword(s):

Impulse Response ◽

Finite Impulse Response ◽

Time Signal ◽

Rate System ◽

Interpolation Filter ◽

Finite Impulse Response Filters ◽

Impulse Response Filters ◽

The Time Domain ◽

Sampling Procedures

Chapter 17 presents the multi-rate signal process, starting with explanations of the up-sampling and down-sampling procedures on a discrete signal in the time domain. The operations of a down-sampler (decimator) and an up-sampler (interpolator) are analysed in the frequency domain, emphasizing the problem of possible aliasing. Complex systems that include both up-sampling and down-sampling are analysed and the problem of complexity reduction is mentioned. The operation of systems that combine an interpolator and an interpolation filter, and a decimator and a decimation lowpass filter, is presented in the time and frequency domains. In particular, the problem of reducing the complexity of a multi-rate system is addressed, and a polyphase decomposition for both finite impulse response filters and infinite impulse response filters is offered as an efficient solution.