High level fault modeling of analog circuits through automated model generation using Chebyshev and Newton interpolating polynomials

Xia, Likun; Farooq, Muhammad; Bell, Ian M.

doi:10.1007/s10470-014-0431-9

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…However, how to obtain the specific content source from the initial music multimedia data, lacking the definition of the music content, has become a huge challenge for the current automatic classification of music multimedia because the music multimedia signal belongs to a way of time sequence, which can be concealed according to its concealment. Using the hidden Markov model, at present, other classification methods are relatively simple, and the characteristics of music multimedia are not accurate [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Automatic Classification and Analysis of Music Multimedia Combined with Hidden Markov Model

Chen

2021

Advances in Multimedia

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Music multimedia is one of the more popular types of digital music. This article is based on the hidden Markov model (HMM) and proposed this kind of music multimedia automatic classification method. The method not only analyzes the characteristics of traditional music in detail but also fully considers the important characteristics of other music. At the same time, it uses bagging to train two groups of HMMs and automatically classifies them to achieve a better classification effect. This paper optimizes the variable parameters from different aspects such as model structure, data form, and model change to obtain the optimal HMM parameter value. This method not only considers the prior knowledge of feature words, word frequency, and number of documents but also fuses the meaning of the feature words into the hidden Markov classification model. Finally, by testing the hidden Markov model used in this paper on the music multimedia data set, the experimental results show that the method in this paper can effectively perform automatic classification according to the melody characteristics of music multimedia.

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Section: Introductionmentioning

confidence: 99%

Automatic Classification and Analysis of Music Multimedia Combined with Hidden Markov Model

Chen

2021

Advances in Multimedia

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“…Fault simulation using high-level models [9], [53], [91], [29], [62], [89], [82], [35], [31], [58], [66], [74], [78], [40], [87], [55], [42], [82], [91], [56] Fault simulation using fault grouping [70], [21], [48], [46], [54], [92], [65], [41], [86], [8], [25], [60] Concurrent and parallel fault simulation [7], [51], [69], [61], [37], [51], [30] Fault sensitivity analysis [11], [75], [33], [49], [26], [28] Monte Carlo simulation [10], [47], [22] DC fault simulation [64]…”

Section: Techniquementioning

confidence: 99%

Analog Defect Injection and Fault Simulation Techniques: A Systematic Literature Review

Azam

Dall'Ora

Fraccaroli

et al. 2024

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Since the last century, the exponential growth of the semiconductor industry has led to the creation of tiny and complex integrated circuits, e.g., sensors, actuators, and smart power. Innovative techniques are needed to ensure the correct functionality of analog devices that are ubiquitous in every smart system. The ISO 26262 standard for functional safety in the automotive context specifies that fault injection is necessary to validate all electronic devices. For decades, standardization of defect modeling and injection mainly focused on digital circuits and, in a minor part, on analog ones. An initial attempt is being made with the IEEE P2427 draft standard that started to give a structured and formal organization to the analog testing field.Various methods have been proposed in the literature to speed up the fault simulation of the defect universe for an analog circuit. A more limited number of papers seek to reduce the overall simulation time by reducing the number of defects to be simulated. This literature survey describes the state-of-the-art of analog defect injection and fault simulation methods. The survey is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodological flow, allowing for a systematic and complete literature survey. Each selected paper has been categorized and presented to provide an overview of all the available approaches. In addition, the limitations of the various approaches are discussed by showing possible future directions.

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“…This is due to some limitations in the current HDLs. For example, in [11] VHDL-AMS is used for fault modeling of analog circuits, where part of the system required modeling in MATLAB. Also in [12], VHDL-AMS is used to design energy efficient sensor nodes optimum performance and then MATLAB optimization toolbox is used.…”

Section: Introductionmentioning

confidence: 99%

Modeling Single Flexible Link Using Hardware Description Language

Al-Junaid¹

2016

IJCDS

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This paper presents a well known model of arm with flexible robotic link modeled in Hardware Description Language (HDL). The system is modeled on behavioural level described as nonlinear DAEs in a new developed hardware description language called SystemC-A. It is an extended version of the C++ based digital simulator SystemC which provides analogue, mixed-signal and mixed-domain modelling capabilities. The paper objective is of twofold, verifying the new language capabilities, and modelling a system of high complexity. The model was compared with SIMULINK/MATLAB and proved to be highly accurate.

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High level fault modeling of analog circuits through automated model generation using Chebyshev and Newton interpolating polynomials

Cited by 5 publications

References 16 publications

Automatic Classification and Analysis of Music Multimedia Combined with Hidden Markov Model

Automatic Classification and Analysis of Music Multimedia Combined with Hidden Markov Model

Analog Defect Injection and Fault Simulation Techniques: A Systematic Literature Review

Modeling Single Flexible Link Using Hardware Description Language

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