scholarly journals Approximate logic synthesis under general error magnitude and frequency constraints

2013 ◽  
Author(s):  
Jin Miao ◽  
Andreas Gerstlauer ◽  
Michael Orshansky
Keyword(s):  
Logic Synthesis ◽  
Frequency Constraints ◽  
Error Magnitude ◽  
General Error

Algorithm of Optimizing Quantum Reversible Logic Synthesis

2009 ◽  
Vol 20 (9) ◽  
pp. 2332-2343
Author(s):  
Zhi-Qiang LI ◽  
Wen-Qian LI ◽  
Han-Wu CHEN
Keyword(s):  
Logic Synthesis ◽  
Reversible Logic ◽  
Reversible Logic Synthesis

Thermal-aware Output Polarity Selection Based on And-Inverter Graph Manipulation

2019 ◽  
Vol 12 (1) ◽  
pp. 30-39 ◽  
Author(s):  
Apangshu Das ◽  
Sambhu Nath Pradhan
Keyword(s):  
Integrated Circuits ◽  
Power Density ◽  
Logic Synthesis ◽  
Programmable Logic Arrays ◽  
Power Switching ◽  
Nsga Ii ◽  
Multi Level ◽  
Search Approach ◽  
Efficient Power ◽  
The Impact

Background: Output polarity of the sub-function is generally considered to reduce the area and power of a circuit at the two-level realization. Along with area and power, the power-density is also one of the significant parameter which needs to be consider, because power-density directly converges to circuit temperature. More than 50% of the modern day integrated circuits are damaged due to excessive overheating. Methods: This work demonstrates the impact of efficient power density based logic synthesis (in the form of suitable polarity selection of sub-function of Programmable Logic Arrays (PLAs) for its multilevel realization) for the reduction of temperature. Two-level PLA optimization using output polarity selection is considered first and compared with other existing techniques and then And-Invert Graphs (AIG) based multi-level realization has been considered to overcome the redundant solution generated in two-level synthesis. AIG nodes and associated power dissipation can be reduced by rewriting, refactoring and balancing technique. Reduction of nodes leads to the reduction of the area but on the contrary increases power and power density of the circuit. A meta-heuristic search approach i.e., Nondominated Sorting Genetic Algorithm-II (NSGA-II) is proposed to select the suitable output polarity of PLA sub-functions for its optimal realization. Results: Best power density based solution saves up to 8.29% power density compared to ‘espresso – dopo’ based solutions. Around 9.57% saving in area and 9.67% saving in power (switching activity) are obtained with respect to ‘espresso’ based solution using NSGA-II. Conclusion: Suitable output polarity realized circuit is converted into multi-level AIG structure and synthesized to overcome the redundant solution at the two-level circuit. It is observed that with the increase in power density, the temperature of a particular circuit is also increases.

scholarly journals Does Head Orientation Influence 3D Facial Imaging? A Study on Accuracy and Precision of Stereophotogrammetric Acquisition

2021 ◽  
Vol 18 (8) ◽  
pp. 4276
Author(s):  
Giuditta Battistoni ◽  
Diana Cassi ◽  
Marisabel Magnifico ◽  
Giuseppe Pedrazzi ◽  
Marco Di Blasio ◽  
...  
Keyword(s):  
Head Rotation ◽  
Anthropometric Measurements ◽  
Head Orientation ◽  
3D Images ◽  
Face Shape ◽  
Operator Error ◽  
Accuracy And Precision ◽  
Error Magnitude ◽  
Repeatability And Reproducibility ◽  
Head Positions

This study investigates the reliability and precision of anthropometric measurements collected from 3D images and acquired under different conditions of head rotation. Various sources of error were examined, and the equivalence between craniofacial data generated from alternative head positions was assessed. 3D captures of a mannequin head were obtained with a stereophotogrammetric system (Face Shape 3D MaxiLine). Image acquisition was performed with no rotations and with various pitch, roll, and yaw angulations. On 3D images, 14 linear distances were measured. Various indices were used to quantify error magnitude, among them the acquisition error, the mean and the maximum intra- and inter-operator measurement error, repeatability and reproducibility error, the standard deviation, and the standard error of errors. Two one-sided tests (TOST) were performed to assess the equivalence between measurements recorded in different head angulations. The maximum intra-operator error was very low (0.336 mm), closely followed by the acquisition error (0.496 mm). The maximum inter-operator error was 0.532 mm, and the highest degree of error was found in reproducibility (0.890 mm). Anthropometric measurements from alternative acquisition conditions resulted in significantly equivalent TOST, with the exception of Zygion (l)–Tragion (l) and Cheek (l)–Tragion (l) distances measured with pitch angulation compared to no rotation position. Face Shape 3D Maxiline has sufficient accuracy for orthodontic and surgical use. Precision was not altered by head orientation, making the acquisition simpler and not constrained to a critical precision as in 2D photographs.

Hypothesis testing with error correction models

2021 ◽  
pp. 1-9
Author(s):  
Patrick W. Kraft ◽  
Ellen M. Key ◽  
Matthew J. Lebo
Keyword(s):  
Hypothesis Testing ◽  
Error Correction ◽  
Null Hypothesis ◽  
Alternative Hypothesis ◽  
Correction Coefficient ◽  
Correction Model ◽  
Long Run ◽  
Independent Variable ◽  
The Right ◽  
General Error

Abstract Grant and Lebo (2016) and Keele et al. (2016) clarify the conditions under which the popular general error correction model (GECM) can be used and interpreted easily: In a bivariate GECM the data must be integrated in order to rely on the error correction coefficient, $\alpha _1^\ast$ , to test cointegration and measure the rate of error correction between a single exogenous x and a dependent variable, y. Here we demonstrate that even if the data are all integrated, the test on $\alpha _1^\ast$ is misunderstood when there is more than a single independent variable. The null hypothesis is that there is no cointegration between y and any x but the correct alternative hypothesis is that y is cointegrated with at least one—but not necessarily more than one—of the x's. A significant $\alpha _1^\ast$ can occur when some I(1) regressors are not cointegrated and the equation is not balanced. Thus, the correct limiting distributions of the right-hand-side long-run coefficients may be unknown. We use simulations to demonstrate the problem and then discuss implications for applied examples.

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