Statistical Compact Model Extraction for Skewed Gaussian Variations

2014 ◽  
pp. 207-209
Author(s):  
V. Janakiraman ◽  
Shrinivas J. Pandharpure ◽  
Josef Watts
Keyword(s):  
Compact Model ◽  
Model Extraction

A non-iterative physical procedure for RF CMOS compact model extraction using BSIM6

2012 ◽  
Author(s):  
Sriramkumar Venugopalan ◽  
Krishnanshu Dandu ◽  
Samuel Martin ◽  
Richard Taylor ◽  
Claude Cirba ◽  
...  
Keyword(s):  
Compact Model ◽  
Rf Cmos ◽  
Model Extraction

Vector Fitting Based Adaptive Frequency Sampling for Compact Model Extraction on HPC Systems

2012 ◽  
Vol 48 (2) ◽  
pp. 431-434 ◽  
Author(s):  
Gabriela Ciuprina ◽  
Daniel Ioan ◽  
Ioan Alexandru Lazar ◽  
Cosmin Bogdan Dita
Keyword(s):  
Compact Model ◽  
Model Extraction ◽  
Vector Fitting ◽  
Frequency Sampling

Parameter set and data sampling strategy for accurate yet efficient statistical MOSFET compact model extraction

2010 ◽  
Vol 54 (3) ◽  
pp. 307-315 ◽  
Author(s):  
B. Bindu ◽  
B. Cheng ◽  
G. Roy ◽  
X. Wang ◽  
S. Roy ◽  
...  
Keyword(s):  
Sampling Strategy ◽  
Compact Model ◽  
Data Sampling ◽  
Model Extraction

scholarly journals Statistical compact model extraction for skew‐normal distributions

2020 ◽  
Vol 14 (5) ◽  
pp. 576-585
Author(s):  
Koduru Revanth ◽  
Viraraghavan Janakiraman
Keyword(s):  
Compact Model ◽  
Normal Distributions ◽  
Model Extraction ◽  
Skew Normal Distributions ◽  
Skew Normal

scholarly journals FinFET Centric Variability-Aware Compact Model Extraction and Generation Technology Supporting DTCO

2015 ◽  
Vol 62 (10) ◽  
pp. 3139-3146 ◽  
Author(s):  
Xingsheng Wang ◽  
Binjie Cheng ◽  
David Reid ◽  
Andrew Pender ◽  
Plamen Asenov ◽  
...  
Keyword(s):  
Compact Model ◽  
Model Extraction ◽  
Generation Technology

Statistical Compact Model Extraction: A Neural Network Approach

2012 ◽  
Vol 31 (12) ◽  
pp. 1920-1924 ◽  
Author(s):  
Janakiraman Viraraghavan ◽  
Shrinivas J. Pandharpure ◽  
Josef Watts
Keyword(s):  
Neural Network ◽  
Compact Model ◽  
Network Approach ◽  
Neural Network Approach ◽  
Model Extraction

Exhaustive and Systematic Accuracy Verification and Enhancement of STI Stress Compact Model for General Realistic Layout Patterns

2010 ◽  
Vol E93-C (8) ◽  
pp. 1349-1358
Author(s):  
Kenta YAMADA ◽  
Toshiyuki SYO ◽  
Hisao YOSHIMURA ◽  
Masaru ITO ◽  
Tatsuya KUNIKIYO ◽  
...  
Keyword(s):  
Compact Model

Sky Segmentation for Enhanced Depth Reconstruction and Bokeh Rendering with Efficient Architectures

2020 ◽  
Vol 2020 (14) ◽  
pp. 378-1-378-7
Author(s):  
Tyler Nuanes ◽  
Matt Elsey ◽  
Radek Grzeszczuk ◽  
John Paul Shen
Keyword(s):  
Real Time ◽  
Mobile Device ◽  
Computational Cost ◽  
False Positives ◽  
Compact Model ◽  
High Quality ◽  
False Negatives ◽  
Trade Off ◽  
Depth Reconstruction ◽  
Binary Classifiers

We present a high-quality sky segmentation model for depth refinement and investigate residual architecture performance to inform optimally shrinking the network. We describe a model that runs in near real-time on mobile device, present a new, highquality dataset, and detail a unique weighing to trade off false positives and false negatives in binary classifiers. We show how the optimizations improve bokeh rendering by correcting stereo depth misprediction in sky regions. We detail techniques used to preserve edges, reject false positives, and ensure generalization to the diversity of sky scenes. Finally, we present a compact model and compare performance of four popular residual architectures (ShuffleNet, MobileNetV2, Resnet-101, and Resnet-34-like) at constant computational cost.

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