Multiple channel error-correction algorithms for LCC decoding of Reed-Solomon codes and its high-speed architecture design

2017 ◽  
Vol 11 (9) ◽  
pp. 1407-1415 ◽  
Author(s):  
Lingyu Wang ◽  
Wei Zhang ◽  
Yang Wang ◽  
Yan Hu ◽  
Yanyan Liu
Keyword(s):  
Error Correction ◽  
High Speed ◽  
Architecture Design ◽  
Channel Error ◽  
Multiple Channel ◽  
Reed Solomon Codes

FAST ALGORITHM ANALYSIS AND BIT-SERIAL ARCHITECTURE DESIGN FOR SUB-PIXEL MOTION ESTIMATION IN H.264

2010 ◽  
Vol 19 (08) ◽  
pp. 1665-1687 ◽  
Author(s):  
MOHAMMAD REZA HOSSEINY FATEMI ◽  
HASAN F. ATES ◽  
ROSLI SALLEH
Keyword(s):  
Motion Estimation ◽  
High Speed ◽  
Reference Frames ◽  
Optimization Techniques ◽  
Algorithm Analysis ◽  
Architecture Design ◽  
Memory Requirement ◽  
Computational Budget ◽  
Bit Serial ◽  
Operation Frequency

The sub-pixel motion estimation (SME), together with the interpolation of reference frames, is a computationally extensive part of the H.264 encoder that increases the memory requirement 16-times for each reference frame. Due to the huge computational complexity and memory requirement of the H.264 SME, its hardware architecture design is an important issue especially in high resolution or low power applications. To solve the above difficulties, we propose several optimization techniques in both algorithm and architecture levels. In the algorithm level, we propose a parabolic based algorithm for SME with quarter-pixel accuracy which reduces the computational budget by 94.35% and the memory access requirement by 98.5% in comparison to the standard interpolate and search method. In addition, a fast version of the proposed algorithm is presented that reduces the computational budget 46.28% further while maintaining the video quality. In the architecture level, we propose a novel bit-serial architecture for our algorithm. Due to advantages of the bit-serial architecture, it has a low gate count, high speed operation frequency, low density interconnection, and a reduced number of I/O pins. Also, several optimization techniques including the sum of absolute differences truncation, source sharing exploiting and power saving techniques are applied to the proposed architecture which reduce power consumption and area. Our design can save between 57.71–90.01% of area cost and improves the macroblock (MB) processing speed between 1.7–8.44 times when compared to previous designs. Implementation results show that our design can support real time HD1080 format with 20.3 k gate counts at the operation frequency of 144.9 MHz.

scholarly journals Economic Growth and Unemployment Nexus in USA

2019 ◽  
Vol 8 (4) ◽  
pp. 1317-1325
Keyword(s):  
Growth Rate ◽  
Error Correction ◽  
Unemployment Rate ◽  
High Speed ◽  
Empirical Relationship ◽  
Var Model ◽  
Output Gap ◽  
Causality Test ◽  
Vector Error Correction ◽  
Vector Error

Empirical relationship between unemployment and growth is not pronounced as we investigate the economic scenario of the nations. Author attempted to relate US unemployment rate to the growth during 1948-2016 by using bivariate and log regression models, Bai-Perron Model, Granger Causality test, Johansen cointegration test, vector auto regression and vector error correction models. Even, author also verified relationship between unemployment gap, output gap and growth in USA during the same period. Data on US unemployment rate, GDP and growth rate have been taken from Bureau of US census during 1948-2016. Data on US natural rate of unemployment was taken from Fed Bank of St.Louis from 1949 to 2016.The paper concludes that US unemployment rate is increasing at the rate of 0.507 per cent per annum and it has upward structural break in 1971.The nexus follows the Okun’s law in USA. US unemployment is negatively related with growth rate during 1948-2016.Their relationships are causal and cointegrated. VAR model is stable and stationary. Residual test showed non-normality and autocorrelations.Moreover, author showed negative relation between growth and unemployment gap in USA during 1949-2016.They have no causality and cointegration. Their VAR model is stable and stationary. The residual test proved non-normality and auto-correlation problems. Perceptible output gap influences unemployment gap negatively during 1949-2016 .It has significant bi-directional causality and one cointegrating equation. In Vector error correction model, error corrections are significant with high speed having stability, autocorrelation and non-normality. The rate of decline in unemployment rate due to increased growth rate in USA during 1948-2016 was marginal.

Sign in / Sign up

Export Citation Format

Share Document