An Introduction to the Mathematics of Digital Signal Processing: Part II: Sampling, Transforms, and Digital Filtering

1978 ◽  
Vol 2 (2) ◽  
pp. 38 ◽  
Author(s):  
F. R. Moore
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Digital Filtering

scholarly journals A Method of Increasing Digital Filter Performance Based on Truncated Multiply-Accumulate Units

2020 ◽  
Vol 10 (24) ◽  
pp. 9052
Author(s):  
Pavel Lyakhov ◽  
Maria Valueva ◽  
Georgii Valuev ◽  
Nikolai Nagornov
Keyword(s):  
Signal Processing ◽  
Theoretical Analysis ◽  
Digital Signal Processing ◽  
Digital Filter ◽  
Digital Filters ◽  
Digital Signal ◽  
Digital Filtering ◽  
Filter Performance ◽  
Filter Architecture ◽  
Hardware Costs

This paper proposes new digital filter architecture based on a modified multiply-accumulate (MAC) unit architecture called truncated MAC (TMAC), with the aim of increasing the performance of digital filtering. This paper provides a theoretical analysis of the proposed TMAC units and their hardware simulation. Theoretical analysis demonstrated that replacing conventional MAC units with modified TMAC units, as the basis for the implementation of digital filters, can theoretically reduce the filtering time by 29.86%. Hardware simulation showed that TMAC units increased the performance of digital filters by up to 10.89% compared to digital filters using conventional MAC units, but were associated with increased hardware costs. The results of this research can be used in the theory of digital signal processing to solve practical problems such as noise reduction, amplification and suppression of the frequency spectrum, interpolation, decimation, equalization and many others.

scholarly journals Development of a method for synthesis the FIR filters with a cascade structure based on genetic algorithm

2021 ◽  
Vol 4 (2(60)) ◽  
pp. 6-11
Author(s):  
Ruslan Petrosian ◽  
Vladyslav Chukhov ◽  
Arsen Petrosian
Keyword(s):  
Genetic Algorithm ◽  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Filters ◽  
Computation Time ◽  
Digital Signal ◽  
Digital Filtering ◽  
Fir Filters ◽  
Filter Synthesis ◽  
Cascade Structure

The object of research is the process of digital signal processing. The subject of research is methods of synthesis of digital filters with a finite impulse response based on a genetic algorithm. Digital filtering is one of the tasks of digital signal processing. FIR filters are always stable and provide a constant group delay. There are various methods for synthesizing digital filters, but they are all aimed at synthesizing filters with a direct structure. One of the most problematic areas of a digital filter with a direct structure in digital processing is the high sensitivity of the filter characteristics to inaccuracies in setting the filter coefficients. Genetic algorithm-based filter synthesis methods use an ideal filter as the approximated filter. This approach has a number of disadvantages: it complicates the search for an optimal solution; computation time increases. The study used random search method, which is the basis of genetic algorithm (used for solving optimization problems); theory of digital filtering in filter analysis; numerical methods for modeling in a Python program. Prepared synthesis method FIR filter with the cascade structure, which is less sensitive to the effect of finite bit width. Computation time was reduced. This is due to the fact that the proposed method searches for the most suitable filter coefficients based on a genetic algorithm and has a number of features, in particular, it is proposed to use a piecewise-linear function as an approximated amplitude-frequency response. This makes it possible to reduce the number of populations of the genetic algorithm when searching for a solution. The synthesis of an FIR filter with a cascade structure based on a genetic algorithm showed that for a 24-order filter it took about 30–40 generations to get the filter parameters close to the optimal values. In comparison with classical methods of filter synthesis, the following advantages are provided: calculations of the coefficients of a filter with a cascade structure directly, the possibility of optimizing coefficients with limited bit depth.

The Performance of near Infrared Analysers Can Be Improved by Digital Filtering Techniques

1998 ◽  
Vol 6 (1) ◽  
pp. 97-104 ◽  
Author(s):  
M. Känsäkoski ◽  
O. Voutilainen ◽  
T. Seppänen
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Filters ◽  
Near Infrared ◽  
Matched Filter ◽  
Digital Signal ◽  
Digital Filtering ◽  
Measurement Signal ◽  
On Line ◽  
Filtering Techniques

On-line near infrared (NIR) analysers are used widely for quantitative composition measurements in real-time process control systems. The accuracy and repeatability of the measurements are amongst the most important factors when evaluating the total performance of these analysers, but the lower detection limit is often limited by noise in the measurement signal. There are two major alternatives for reducing noise in an optical analyser: prevention of noise contamination and post-processing of the signal by filtering. In the second alternative, the measurement signal can be post-processed by digital filtering techniques, for example, to enhance the desired signal component. Although digital signal processing (DSP) technology offers many advantages for on-line process measurements, the behaviour of the signal must be understood thoroughly before a successful application of this technology can be developed. A digital filtering technique called matched filter was used in an experimental set-up. The performance of this filter was compared to an analog filtering of a pulse shaped signal. Experimental data were collected and filtered with a novel digital spectrometer which consists of a modulated light source, a spectrograph, a linear array detector and the analog and digital signal processing electronics needed to control and filter the signal. In this case the matched filter gave a clear improvement of 2.2–4.6 dB in the signal-to-noise ratio (SNR) relative to an analog lock-in amplifier. Among the other advantages afforded by digital filters are that they are programmable, easy to design, test and implement on a PC and do not suffer from drift. Also digital filters are extremely stable with respect to both time and temperature and versatile in their ability to process signals in a variety of ways.

Digital Signal Processing

2009 ◽  
pp. 53-68
Author(s):  
Terrence D. Lagerlund
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Frequency Domain ◽  
Time Domain ◽  
Clinical Neurophysiology ◽  
Digital Signal ◽  
Digital Filtering ◽  
Digital Processing ◽  
Domain Analysis ◽  
Frequency Domain Analysis

This chapter reviews the principles of digitization, the design of digitally based instruments for clinical neurophysiology, and several common uses of digital processing, including averaging, digital filtering, and some types of time-domain and frequency-domain analysis. An understanding of these principles is necessary to select and use digitally based instruments appropriately and to understand their unique features.

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