Application of MATLAB in Digital Signal Processing

2012 ◽  
Vol 490-495 ◽  
pp. 182-185
Author(s):  
Cai Liao ◽  
Yi Mei Song ◽  
Wei Wei Yue ◽  
Dong Bo Zhou ◽  
Dan Ping Liu

The digital filter is one of the most significant applications of digital signal processing (DSP). The design process is very complex involving the model approximation, parameter selection, computer simulation and a series of work. This paper introduces an efficient design method for the digital filter (IIR and FIR) based on the Signal Processing Toolbox of MATLAB, which makes design easy, fast and greatly reduces the amount of design work, and then proves it by practical examples.

1984 ◽  
Vol 21 (1) ◽  
pp. 47-61 ◽  
Author(s):  
Trevor J. Terrell ◽  
Robert J. Simpson

The concepts of single-chip digital signal processing are presented via a student-oriented tutorial/laboratory case study. This involves the design of a highpass digital filter using the first-difference design method and its implementation using the NEC μPD7720 Signal Processor.


2013 ◽  
Vol 481 ◽  
pp. 225-229
Author(s):  
Juan Zhang ◽  
Wen Peng Fu ◽  
Rong Jun Zhang

A method of designing onedimensional photonic crystal is presented from the perspective of Z-domain and digital signal processing. The optical structure and structural parameters for the desired filtering spectrum in reflection can be directly obtained by using the design method. A design example is given in the paper to verify the method.


2020 ◽  
Vol 10 (24) ◽  
pp. 9052
Author(s):  
Pavel Lyakhov ◽  
Maria Valueva ◽  
Georgii Valuev ◽  
Nikolai Nagornov

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.


Author(s):  
Benjamin A. Coifman

A new methodology has been developed for smoothing loop detector data based on digital signal processing. After introducing basic signal processing theory, existing smoothing techniques like fixed-time averages, cumulative sums, and moving-time averages—all subsets of the larger digital signal processing methodology—are described. Nontraditional smoothing techniques based on custom digital filter design are then presented, specifically, low-pass filters that “pass” slowly changing features of the detector data unchanged while attenuating rapidly changing features. Custom digital filter design gives more control over the smoothing process than do traditional smoothing methods. In particular, the amount of amplification or attenuation at a given frequency (e.g., rapidly or slowly changing features) can be set. Whether a custom filter or a traditional smoothing process is used, an understanding of the frequency response can increase the usefulness of the resulting data by clarifying the limitations of the given smoothing process. To illustrate this, several smoothing processes are presented and contrasted using the same data set. The use of a custom digital filter is demonstrated in three practical applications: an examination of the bivariate flow-occupancy relationship and use of the filtering process to eliminate unstable disturbances from the data set, speed estimation from a single detector under congested conditions, and temporal issues relating to shock wave and fluctuation propagation specifically.


2007 ◽  
Author(s):  
Chao-Chang Hu ◽  
Yi C. Fang ◽  
Chen-Mu Tsai ◽  
Han-Ching Lin ◽  
Han-Wei Su ◽  
...  

2012 ◽  
Vol 503-504 ◽  
pp. 228-231 ◽  
Author(s):  
Shan Ren ◽  
Xin Zhao ◽  
Jie Jiang ◽  
Dong Jin Zhao

Digital filter is one of the most important parts of digital signal processing. In practice, digital signal processing often need to limit the signal observation time interval within a certain time, choose only one period of signal that signal data will be truncated, this process is equivalent to plus window function operation to signal. In order to obtain finite unit sample response, need to truncate the infinite unit sample response sequence by window function. This paper proposes the method of using window function to design FIR Band-pass filter based on MATLAB, according to the design basic principle of FIR digital filter. Filtering processing for measured signal showed that filtering effect of the filter achieved the expected results.


2012 ◽  
Vol 490-495 ◽  
pp. 1867-1870 ◽  
Author(s):  
Shan Ren ◽  
Xin Zhao ◽  
Wen Bin Zhang

Digital filter is one of the most important parts of digital signal processing. This paper proposes the method of using window function to design FIR filter based on MATLAB, according to the design basic principle of FIR digital filter. Filtering processing for measured signal showed that filtering effect of the filter achieved the expected results.


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