Binning algorithm for accurate computer aided device modeling

Mendhurwar, Kaustubha; Devabhaktuni, V.K.; Raut, R.

doi:10.1109/iscas.2008.4542032

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…Various parameters of detailed PMOS and NMOS models are swept on a wider range (details can be found in [36]) using HSPICE. Highly accurate simulation data obtained from HSPICE is stored in the form of a database.…”

Section: Analog Ic Design Flowmentioning

confidence: 99%

“…2. Neural models are developed using the algorithms proposed in our previous papers [36][37][38][39][40][41]. 3.…”

Section: Analog Ic Design Flowmentioning

confidence: 99%

“…The simulation data is generated using a detailed HSPICE model, which then helps us to develop highly accurate neural models using the algorithms described in our previous papers [36][37][38][39]. A datasheet of simulation data is generated by sweeping the parameters within their minimum and maximum usable values.…”

Section: Ann Based Cadmentioning

confidence: 99%

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A new approach to sizing analog CMOS building blocks using pre-compiled neural network models

Mendhurwar

Sundani

Aggarwal

et al. 2011

Analog Integr Circ Sig Process

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There has been a constant endeavor towards improving the available circuit design automation tools to match technological advancements in the electronic industry. However, inadequate research efforts in the analog domain are holding back the exploitation of advanced technologies. A dearth of design expertise in the analog domain is the principal driving force for the growth of Design Automation (DA) tools. Transistor sizing is one of the most crucial steps in the analog IC design. In this paper, we put forward a new computer aided design framework for the sizing of transistors in MOS Integrated Circuit (IC) amplifiers by incorporating powerful modeling capabilities of Artificial Neural Networks (ANN). ANNs have proven to be efficient and accurate modeling tools in several applications. The proposed tool is capable of directly computing transistor related design parameters, of the MOS IC amplifier and associated peripheral circuitry. The proposed tool thus avoids several time-consuming simulations and/or tuning runs at the very bottom level of analog IC amplifier implementation, using a given CMOS process. It also reduces manual intervention in the design process, thus enhancing the automation of the design process. This paper presents design examples of several analog IC functional modules that are developed and verified successfully.

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Section: Analog Ic Design Flowmentioning

confidence: 99%

“…2. Neural models are developed using the algorithms proposed in our previous papers [36][37][38][39][40][41]. 3.…”

Section: Analog Ic Design Flowmentioning

confidence: 99%

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A new approach to sizing analog CMOS building blocks using pre-compiled neural network models

Mendhurwar

Sundani

Aggarwal

et al. 2011

Analog Integr Circ Sig Process

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Two-Dimensional Data Binning for the Analysis of Genome Architecture in Filamentous Plant Pathogens and Other Eukaryotes

Saunders

Win

Kamoun

et al. 2014

Methods in Molecular Biology

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Genome architecture often reflects an organism's lifestyle and can therefore provide insights into gene function, regulation, and adaptation. In several lineages of plant pathogenic fungi and oomycetes, characteristic repeat-rich and gene-sparse regions harbor pathogenicity-related genes such as effectors. In these pathogens, analysis of genome architecture has assisted the mining for novel candidate effector genes and investigations into patterns of gene regulation and evolution at the whole genome level. Here we describe a two-dimensional data binning method in R with a heatmap-style graphical output to facilitate analysis and visualization of whole genome architecture. The method is flexible, combining whole genome architecture heatmaps with scatter plots of the genomic environment of selected gene sets. This enables analysis of specific values associated with genes such as gene expression and sequence polymorphisms, according to genome architecture. This method enables the investigation of whole genome architecture and reveals local properties of genomic neighborhoods in a clear and concise manner.

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Binning Based Data Driven Machine Learning Models for Solar Radiation Forecasting in India

Munshi,

Moharil

2024

Iran J Sci Technol Trans Electr Eng

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Binning algorithm for accurate computer aided device modeling

Cited by 4 publications

References 7 publications

A new approach to sizing analog CMOS building blocks using pre-compiled neural network models

A new approach to sizing analog CMOS building blocks using pre-compiled neural network models

Two-Dimensional Data Binning for the Analysis of Genome Architecture in Filamentous Plant Pathogens and Other Eukaryotes

Binning Based Data Driven Machine Learning Models for Solar Radiation Forecasting in India

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