Pattern Search Automation for Combinational Logic Analysis

2018 ◽  
Author(s):  
Ravikumar Venkat Krishnan ◽  
Seah Yi Xuan ◽  
Lim Gabriel ◽  
Tan Abel ◽  
Lua Winson ◽  
...  
Keyword(s):  
Search Algorithm ◽  
Pattern Search ◽  
Combinational Logic ◽  
Laser Interaction ◽  
Reference Library ◽  
Standard Cells ◽  
Laser Probing ◽  
Precise Understanding ◽  
Turn Around Time ◽  
Probe Placement

Abstract Combinational logic analysis (CLA) using laser voltage probing allows studying standard cells such as NOR or NAND gates as a whole, instead of individual transistors. The process involves building a reference library of laser probing (LP) waveforms and comparing them to signals from the real device. While CLA has greatly increased the success rate and turn-around time for LP, there are difficulties in signal interpretation. This is partly due to the lack of precise understanding of the laser interaction area and probe placement and partly due to difficulties identifying the correct logic states in the waveform. In this work, we have significantly improved the CLA process by first predicting the shape of the waveform based on laser interaction with the target circuitry and second, implementing an automated pattern search algorithm to further increase the speed and reliability of CLA using LP.

scholarly journals IDENTIFICATION OF A ROBUST LICHEN INDEX FOR THE DECONVOLUTION OF LICHEN AND ROCK MIXTURES USING PATTERN SEARCH ALGORITHM (CASE STUDY: GREENLAND)

2016 ◽  
Vol XLI-B7 ◽  
pp. 973-979
Author(s):  
S. Salehi ◽  
M. Karami ◽  
R. Fensholt
Keyword(s):  
Search Algorithm ◽  
Mineral Exploration ◽  
Optimization Procedure ◽  
Hyperspectral Data ◽  
Pattern Search ◽  
Rock Outcrops ◽  
Bare Rock ◽  
Mixed Pixel ◽  
Mixing Ratios ◽  
Linear Mixtures

Lichens are the dominant autotrophs of polar and subpolar ecosystems commonly encrust the rock outcrops. Spectral mixing of lichens and bare rock can shift diagnostic spectral features of materials of interest thus leading to misinterpretation and false positives if mapping is done based on perfect spectral matching methodologies. Therefore, the ability to distinguish the lichen coverage from rock and decomposing a mixed pixel into a collection of pure reflectance spectra, can improve the applicability of hyperspectral methods for mineral exploration. The objective of this study is to propose a robust lichen index that can be used to estimate lichen coverage, regardless of the mineral composition of the underlying rocks. The performance of three index structures of ratio, normalized ratio and subtraction have been investigated using synthetic linear mixtures of pure rock and lichen spectra with prescribed mixing ratios. Laboratory spectroscopic data are obtained from lichen covered samples collected from Karrat, Liverpool Land, and Sisimiut regions in Greenland. The spectra are then resampled to Hyperspectral Mapper (HyMAP) resolution, in order to further investigate the functionality of the indices for the airborne platform. In both resolutions, a Pattern Search (PS) algorithm is used to identify the optimal band wavelengths and bandwidths for the lichen index. The results of our band optimization procedure revealed that the ratio between R<sub>894-1246</sub> and R<sub>1110</sub> explains most of the variability in the hyperspectral data at the original laboratory resolution (R<sup>2</sup>=0.769). However, the normalized index incorporating R<sub>1106-1121</sub> and R<sub>904-1251</sub> yields the best results for the HyMAP resolution (R<sup>2</sup>=0.765).

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