This work explores a set of approximate adders (COPY adder, error-tolerant adder - ETA, lower-part OR adder - LOA, truncation - Trunc, and approximate parallel prefix adder - AxPPA) to enhance a VLSI design for ECG si...
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ISBN:
(数字)9798350391695
ISBN:
(纸本)9798350391701
This work explores a set of approximate adders (COPY adder, error-tolerant adder - ETA, lower-part OR adder - LOA, truncation - Trunc, and approximate parallel prefix adder - AxPPA) to enhance a VLSI design for ECG signal preprocessing based on Pan-Tompkins algorithm (AxPTA) to improve energy efficiency and QRS complex detection. Validation with the MIT-BIH database confirms that the AxPTA design maintains excellent sensitivity and positive predictivity with reduced energy consumption and circuit area. The AxPTA with AxPPA achieves a 10.22% reduction in circuit size and saves 85.06% energy, with an acceptable 1.32% precision deviation. These results suggest that the AxPPA significantly boosts energy efficiency in the AxPTA design for ECG analysis, supporting the development of portable devices for continuous heart monitoring and cardiovascular disease prevention.
This work investigates the design of approximate arithmetic operator units used in the VLSI modular reduction (AxMOD) architecture. The AxMOD architecture herein proposed explores the following arithmetic operators: i...
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ISBN:
(数字)9798350391695
ISBN:
(纸本)9798350391701
This work investigates the design of approximate arithmetic operator units used in the VLSI modular reduction (AxMOD) architecture. The AxMOD architecture herein proposed explores the following arithmetic operators: i) two approximate iterative-based fixed-point and Goldschmidt (GLD) dividers, ii) five approximate adders (AxA): COPY adder, error-tolerant adder (ETA), lower-part OR adder (LOA), truncation (Trunc), and approximate parallel prefix adder (AxPPA), and iii) five approximate multipliers of approximate radix-4 multiplier units (AxRMU), dynamic range unbiased multiplier (DRUM), rounding-based approximate (RoBA), truncated multiplier (Trunc), and the leading one-bit based approximate (LoBA). Our demonstration of AxMOD’s efficiency using approximate arithmetic operators from the Pareto-optimal front illustrates the area and power-quality trade-off. Our results reveal that in fixed-point arithmetic, AxRMU with K = 16 and Trunc adder with K = 8 deliver energy savings of up to 4.14× compared to the state-of-the-art.
Approximate computing (AxC) offers opportunities to enhance computing efficiency by exploiting inherent error resilience. This study examines the security implications of AxC, focusing on adders, where Hardware Trojan...
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ISBN:
(数字)9798350391695
ISBN:
(纸本)9798350391701
Approximate computing (AxC) offers opportunities to enhance computing efficiency by exploiting inherent error resilience. This study examines the security implications of AxC, focusing on adders, where Hardware Trojan Horses (HTH) present significant risks. We propose a framework to inject HTH into approximate adders (AxAs), specifically the Approximate Parallel Prefix Adder (AxPPA), and assess their impact. The framework, implemented in MATLAB (code available at ***/MorganaMacedo/AxPPA_HTH), evaluates HTH injection into AxAs, analyzing error metrics (SSIM, NCC, MSE, MAE, and error-probability) and conducting logic-synthesis (LS) analysis to detect physical anomalies indicative of HTH presence. Our results demonstrate AxPPA’s resilience against HTH injection, with detection thresholds varying with approximation bit size. LS analysis shows AxPPA effectively detects HTHs across all bit approximations, outperforming LOA, particularly at K=16. AxPPA also achieves superior energy savings of 31.95% compared to LOA and notable area savings, highlighting its efficacy in HTH detection and performance optimization.
This work introduces a combined version of approximate adders (AxAs), joining approximate parallel prefix adders (AxPPA) with other AxAs from the literature (COPY, Truncation - TRUNC, and lower-part OR adder - LOA). W...
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ISBN:
(数字)9798350377200
ISBN:
(纸本)9798350377217
This work introduces a combined version of approximate adders (AxAs), joining approximate parallel prefix adders (AxPPA) with other AxAs from the literature (COPY, Truncation - TRUNC, and lower-part OR adder - LOA). We call this approach M-AxPPA (modified approximate parallel prefix adder) and investigate three specific versions: M-AxPPA-COPY, M-AxPPA-TRUNC, and M-AxPPA-LOA. We evaluate 315 different configurations, comparing our novel M-AxPPA to other AxAs proposed in the literature. We present pseudocode examples and investigate the accuracy quality, incorporating metrics like SSIM, NCC, MAE, MRE, and MRED. Additionally, we perform a trade-off analysis between accuracy quality and logic synthesis outcomes, underscoring the advantages of our M-AxPPA, notably the outstanding accuracy achieved by M-AxPPA-LOA (approaching 100%), with a substantial energy-saving.
In recent years, 3D point cloud content has gained attention thanks to applications such as virtual, augmented or mixed reality, real-time immersive communications, and autonomous driving systems. However, raw point c...
In recent years, 3D point cloud content has gained attention thanks to applications such as virtual, augmented or mixed reality, real-time immersive communications, and autonomous driving systems. However, raw point clouds comprise large amount of data, and compression is mandatory to allow efficient transmission and storage. The MPEG group proposed the standard called Geometry-based Point Cloud Compression (G-PCC) implemented in the Test Condition Category 1 and 3 (TMC13) software. TMC13 can significantly reduce the amount of data in static point clouds, but requires a high computational cost making real-time compression unfeasible, especially for devices with limited computational power and energy resources. This paper presents a computational cost and coding efficiency evaluation of the G-PCC coding tools. Two main contributions are presented: first, a coding efficiency analysis of different G-PCC tools; second, a complexity profiling of the G-PCC coding steps aimed at understanding the computational effort distribution. This work provides the first complexity assessment of G-PCC. The presented results can help in the proposal of complexity reduction approaches for the development of more efficient versions of G-PCC for real-time purposes.
This study evaluates an agent-based reinforcement learning framework for model-based testing (MBT). The framework's performance was assessed on three key metrics: effectiveness and efficiency in achieving model co...
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Robotic assembly of modular blocks has a great interest in multi-robotic studies in many disciplines. The existing studies primarily focus on context-specific tasks, especially in the self-assembly of robots, from an ...
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Speech emotion recognition (SER) is a Machine Learning (ML) topic that is now receiving a lot of research attention. This can be attributed to its growing capacity, improvements in algorithms, and utilization in pract...
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Demand generation is crucial for organizations, supplying sales teams with well-qualified commercial opportunities. Despite the wide variety of existing opportunity qualification methodologies, the subjective nature o...
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Lossy video compression introduces visual artifacts that degrade video quality, where deep neural networks (DNNs) are effective in enhancement. However, conventional DNN-based methods often focus on a single video com...
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