Y
Yuan-Ho Chen
Researcher at Chang Gung University
Publications - 47
Citations - 584
Yuan-Ho Chen is an academic researcher from Chang Gung University. The author has contributed to research in topics: Discrete cosine transform & Booth's multiplication algorithm. The author has an hindex of 11, co-authored 46 publications receiving 509 citations. Previous affiliations of Yuan-Ho Chen include National Tsing Hua University & Chung Yuan Christian University.
Papers
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Period Extension and Randomness Enhancement Using High-Throughput Reseeding-Mixing PRNG
TL;DR: A new reseeding-mixing method to extend the system period length and to enhance the statistical properties of a chaos-based logistic map pseudo random number generator (PRNG) attains the best throughput rate of 6.4 Gb/s compared with other nonlinear PRNGs.
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A High-Accuracy Adaptive Conditional-Probability Estimator for Fixed-Width Booth Multipliers
Yuan-Ho Chen,Tsin-Yuan Chang +1 more
TL;DR: A single compensation formula of adaptive conditional-probability estimator (ACPE) applied to fixed-width Booth multiplier is proposed and the ACPE Booth multipliers are applied to two-dimensional (2-D) discrete cosine transform (DCT) to evaluate the system performance.
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A Probabilistic Estimation Bias Circuit for Fixed-Width Booth Multiplier and Its DCT Applications
TL;DR: Implemented in an 8 × 8 2-D discrete cosine transform (DCT) core, the DCT core using the proposed PEB Booth multiplier improves the peak signal-to-noise ratio by 17 dB with only a 2% area penalty compared with the direct-truncated method.
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High Throughput DA-Based DCT With High Accuracy Error-Compensated Adder Tree
TL;DR: By operating the shifting and addition in parallel, an error-compensated adder-tree (ECAT) is proposed to deal with the truncation errors and to achieve low-error and high-throughput discrete cosine transform (DCT) design.
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Hardware Design and Implementation of a Wavelet De-Noising Procedure for Medical Signal Preprocessing
Szi-Wen Chen,Yuan-Ho Chen +1 more
TL;DR: Simulation experiment results produced by applying a set of simulated noise-contaminated electrocardiogram (ECG) signals into the de-noising circuit showed that the circuit could not only meet the requirement of real-time processing, but also achieve satisfactory performance for noise reduction, while the sharp features of the ECG signals can be well preserved.