A generic topology selection method for analog circuits with embedded circuit sizing demonstrated on the OTA example

Author(s):  
Andreas Gerlach ◽  
Juergen Scheible ◽  
Thoralf Rosahl ◽  
Frank-Thomas Eitrich
Author(s):  
Yen-Lung Chen ◽  
Chien-Nan Jimmy Liu

Manually designing the analog/RF and power circuits to meet requirements is often considered a difficult task that takes a lot of time. Several automatic circuit-sizing approaches have been proposed for typical analog circuits to solve this bottleneck, but the performance and yield is unexpected if the non-ideal effects are not considered. In this chapter, an equation-based automatic synthesis approach for analog circuits is proposed. The layout-induced parasitic effects and process variations are also considered simultaneously to guarantee the circuit performance after manufacturing. As shown in the experimental results, the proposed approach successfully solves the unreachable specification in previous work and keeps the performance and yield of the generated circuit even in post-layout simulations. The incurred hardware overhead is also reduced by using the proposed unified approach, which demonstrates the feasibility and efficiency of this approach.


2020 ◽  
Vol 309 ◽  
pp. 05007
Author(s):  
Xirimo Bao ◽  
Chunmei Ning

Acoustic model topology selection work in constructing large vocabulary speech recognition systems is being done empirically or heuristically. In this paper, we propose two improved algorithms, which are based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) respectively, on the basis of our previously proposed algorithms to select and optimize model topologies for small or medium vocabulary speech recognition systems. Our improved algorithms attain the goal of optimizing acoustic model topologies for large vocabulary speech recognition systems mainly through modifying the encoding schemes of our previously proposed algorithms. Experiments on the dialogue corpus of Inner Mongolia University show that, compared with the conventional acoustic model topology selection method, our newly proposed algorithms are able to bring much higher recognition performance for large vocabulary speech recognition systems by optimizing their acoustic model topologies.


2016 ◽  
Vol 11 (4) ◽  
pp. 915-920
Author(s):  
Seung H. Choung ◽  
Sungwoo Bae ◽  
Myungchin Kim

Author(s):  
Prakash Kumar Rout ◽  
Debiprasad Priyabrata Acharya ◽  
Umakanta Nanda

In a system though the analog circuits occupy very less space but they require far more design time than the digital circuits. This is due to the fact that the number of performance measures of an analog circuit is more than those for digital circuits. Predicting and improving the performance, robustness and overall cost of such systems is a major concern in the process of automation. In the automation process, optimization of performances subjected to a verity of environmental constraints is a central task. In this chapter, efficient analog circuit sizing techniques and their optimization are surveyed.


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