scholarly journals Special Issue of Digital Signal Processing on Biology and Image Processing in Medicine

1998 ◽  
Vol 118 (7-8) ◽  
pp. 982-985
Author(s):  
Shin-ichiro Umemura
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Special Issue

Approximate Compressor-Based Multiplier Design Methodology for Error-Resilient Digital Signal Processing

2020 ◽  
Vol 29 (14) ◽  
pp. 2050233
Author(s):  
Zhixi Yang ◽  
Xianbin Li ◽  
Jun Yang
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Digital Signal Processing ◽  
Resource Utilization ◽  
Finite Impulse Response ◽  
Digital Signal ◽  
Fir Filter ◽  
Electrical Performance ◽  
Approximate Computing ◽  
Dsp Applications

As many digital signal processing (DSP) applications such as digital filtering are inherently error-tolerant, approximate computing has attracted significant attention. A multiplier is the fundamental component for DSP applications and takes up the most part of the resource utilization, namely power and area. A multiplier consists of partial product arrays (PPAs) and compressors are often used to reduce partial products (PPs) to generate the final product. Approximate computing has been studied as an innovative paradigm for reducing resource utilization for the DSP systems. In this paper, a 4:2 approximate compressor-based multiplier is studied. Approximate 4:2 compressors are designed with a practical design criterion, and an approximate multiplier that uses both truncation and the proposed compressors for PP reduction is subsequently designed. Different levels of truncation and approximate compression combination are studied for accuracy and electrical performance. A practical selection algorithm is then leveraged to identify the optimal combinations for multiplier designs with better performance in terms of both accuracy and electrical performance measurements. Two real case studies are performed, i.e., image processing and a finite impulse response (FIR) filter. The design proposed in this paper has achieved up to 16.96% and 20.81% savings on power and area with an average signal-to-noise ratio (SNR) larger than 25[Formula: see text]dB for image processing; similarly, with a decrease of 0.3[Formula: see text]dB in the output SNR, 12.22% and 30.05% savings on power and area have been achieved for an FIR filter compared to conventional multiplier designs.

Applications in Digital Image Processing

2013 ◽  
Vol 107 (1) ◽  
pp. 46-53 ◽  
Author(s):  
Jason Silverman ◽  
Gail L. Rosen ◽  
Steve Essinger
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Popular Culture ◽  
Digital Signal Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Signal

Use digital signal processing to capitalize on an exciting intersection of mathematics and popular culture.

scholarly journals Introduction to the Special Issue on Digital Signal Processing in Radio Astronomy

2016 ◽  
Vol 05 (04) ◽  
pp. 1602002 ◽  
Author(s):  
D. C. Price ◽  
J. Kocz ◽  
M. Bailes ◽  
L. J. Greenhill
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Radio Astronomy ◽  
Graphics Processing Units ◽  
High Speed ◽  
High Performance ◽  
Digital Signal ◽  
General Purpose ◽  
Special Issue ◽  
Dsp Systems

Advances in astronomy are intimately linked to advances in digital signal processing (DSP). This special issue is focused upon advances in DSP within radio astronomy. The trend within that community is to use off-the-shelf digital hardware where possible and leverage advances in high performance computing. In particular, graphics processing units (GPUs) and field programmable gate arrays (FPGAs) are being used in place of application-specific circuits (ASICs); high-speed Ethernet and Infiniband are being used for interconnect in place of custom backplanes. Further, to lower hurdles in digital engineering, communities have designed and released general-purpose FPGA-based DSP systems, such as the CASPER ROACH board, ASTRON Uniboard, and CSIRO Redback board. In this introductory paper, we give a brief historical overview, a summary of recent trends, and provide an outlook on future directions.

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