Non-regression approach for the behavioral model generator in mixed-signal system verification

2017 ◽  
Author(s):  
Ling-Yen Song ◽  
Chun Wang ◽  
Chien-Nan Jimmy Liu ◽  
Yun-Jing Lin ◽  
Meng-Jung Lee ◽  
...  
Keyword(s):  
Behavioral Model ◽  
Signal System ◽  
Mixed Signal ◽  
Regression Approach ◽  
Model Generator ◽  
System Verification

Opto-Electro-Mechanical Mixed-Signal System-Level Modeling of Micro Deformable Mirror

2007 ◽  
Author(s):  
Yang He ◽  
Chengyu Jiang ◽  
Weizheng Yuan ◽  
Binghe Ma ◽  
Pengfei Huo
Keyword(s):  
Behavioral Model ◽  
Optical Signal ◽  
System Level ◽  
Deformable Mirror ◽  
Signal System ◽  
Mixed Signal ◽  
Mechanical Coupling ◽  
Mechanical Structure ◽  
System Level Modeling ◽  
Functional Components

This paper presents opto-electro-mechanical mixed-signal system-level modeling of micro deformable mirror, the core component of micro adaptive optics system. Micro deformable mirror element was decomposed into functional components and those components were connected to establish a network to represent the real device. Many mirror element models were put together to represent mirror arrays. Then simulations were implemented in just one emulator. The mirror element was decomposed into three kinds of functional components based on this method, i.e. mechanical structure component (beam and mass), electro-mechanical coupling component (electrostatic gap) and optics component (reflective mirror). The mechanical structure behavioral model, the electro-mechanical coupling behavioral model and optical behavioral model could be set up based on the theory of rigid body relative movement and matrix structural analysis, the law of energy conservation and the theory of ray optics and Gaussian beam, respectively. The models were coded in analog hardware description language and a system-level model of micro deformable mirror was established using these models. Electro-mechanical coupling simulations were implemented to find the resonance frequency, the response time and voltage-displacement relationship of the micro deformable mirror element. The frequency analysis results were compared with ANSYS simulations, and the result proved that the method has near FEM accuracy. Then optical phase modulation simulation of micro deformable mirror arrays was implemented to investigate the relationship between input optical signal and output optical signal when control voltage was applied. The simulation result indicated that the mixed-signal system-level simulation of micro deformable mirror could be accomplished rapidly in this way.

scholarly journals Mixed signal testing system technique with algebraic signature analyzer without carry propagation

2021 ◽  
Author(s):  
Mohammed Faruque Ahmed
Keyword(s):  
Testing System ◽  
Signal System ◽  
High Complexity ◽  
Hardware Complexity ◽  
Mixed Signal ◽  
Algebraic Signature ◽  
Signature Analyzer ◽  
System Technique ◽  
Algebraic Cryptography ◽  
Mixed Signal Testing

Signature Analyzer is an analyzer which is widely used for mixed-signal system testing. But its hardware has high complexity in implementation as the application technique is a system with rules of an arithmetic finite field with arbitrary radix. It’s a challenging task. To avoid this complexity here the project is made based on Algebraic Signature Analyzer that can be used for mixed signal testing and the analyzer doesn’t contain carry propagation circuitry. It improves performance and fault tolerance. This technique is simple and applicable to systems of any size or radix. The hardware complexity is very low compared to the conventional one and can be used in arithmetic/ algebraic cryptography as well as coding

The Multinomial, Multiattribute Logit Choice Model

1979 ◽  
Vol 16 (1) ◽  
pp. 124-132 ◽  
Author(s):  
Dennis H. Gensch ◽  
Wilfred W. Recker
Keyword(s):  
Choice Model ◽  
Behavioral Model ◽  
Multinomial Logit ◽  
Choice Modeling ◽  
Cross Sectional ◽  
Individual Level ◽  
Multiattribute Choice ◽  
Regression Approach ◽  
The Difference ◽  
Sectional Analysis

The authors argue that for the cross-sectional multiattribute approach to choice modeling, the multinomial logit is theoretically and empirically superior to the more commonly used regression approach. Other choice methodologies also are discussed briefly in relation to logit. The difference between individual level (where regression is appropriate) and cross-sectional analysis is recognized. Most marketing managers, because of their research goals, will be using a cross-sectional approach. The derivation of the logit from an underlying behavioral model of choice is illustrated. It is this underlying behavioral model of choice that provides logit with several conceptual advantages for modeling a multiattribute choice structure.

Wavelet-based differential nonlinearity testing of mixed signal system ADCs

2007 ◽  
Author(s):  
Cajetan Akujuobi ◽  
Emad Awada ◽  
Matthew Sadiku ◽  
Warsame Ali
Keyword(s):  
Signal System ◽  
Mixed Signal ◽  
Differential Nonlinearity
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