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Cher Ming Tan – One of the best experts on this subject based on the ideXlab platform.

  • comparison of electromigration simulation in test structure and Actual Circuit
    Applied Mathematical Modelling, 2012
    Co-Authors: Cher Ming Tan
    Abstract:

    Abstract With the rapid increase in Circuit complexity, accurate reliability simulator is necessary as reliability testing for fabricated Circuit is progressively more time and resource consuming. Simple 2D electromigration (EM) simulator has many limitations and most of the 3D EM simulations in the literature are using simple line-via structure which is only part of the real Circuit structure. In this paper, a thorough comparison between simple 3D line-via structure model and 3D Circuit model under different test conditions is performed using class-AB amplifier as an example, and the results showed that simple line-via structure simulation may not always correctly represent the real Circuit failure site.

B. V. Sanker Ram – One of the best experts on this subject based on the ideXlab platform.

  • An ANN Control of Maximum Power Point Tracking for Grid Connected Wind Machines
    International Review of Automatic Control (IREACO), 2014
    Co-Authors: S. Sundeep, G. Madhusudhana Rao, B. V. Sanker Ram
    Abstract:

    This research work investigates about the wind energy conversion system will receive the extensive attention among the various renewable energy systems. The extraction of the maximum possible power available wind energy is an important area of research among the speed sensorless MPPT control of wind area. This paper presents a power point tracking (MPPT) Technique for high performance wind turbturbine with induction machines based on expert systems (Artificial Neural Networks). In this paper, an ANN has been trained in off-line to learn about wind turbturbine characteristics of the torque with the wind speed and the speed of the machine which will be deployed in online for measuring the speed of the wind and torque. The reference speed of the machine is then calculated based on the control of the signal power feedback (PSF). Voltage oriented control of the machine is further integrated with an expert sensorless technique. The proposed method was simulated and conformed on the Actual Circuit in online

Noëlle Lewis – One of the best experts on this subject based on the ideXlab platform.

  • Theoretical study and optimisation of a standard deviation estimator Circuit for adaptive threshold spike detection
    International Journal of Circuit Theory and Applications, 2016
    Co-Authors: François Rummens, Stéphane Ygorra, Sylvie Renaud, Hol C. Mayiss Boussamba, Noëlle Lewis
    Abstract:

    Summary This paper presents a theoretical study and the resulting architecture of an analogue-based standard deviation (SD) estimator, typically used in biomedical spike detectors to assess the noise level of bioelectrical recordings online. This well-known Circuit generated a significant inaccuracy, so the aim was to increase the efficiency of spike detection through proper calculation of the noise SD, by developing a rigorous, original theoretical study. The approach consisted of establishing behavioural models for the SD estimation Circuit to obtain a transfer function and compare different controllers. This modelling approach also highlighted the parameters available and the impact of their relationships on design optimisation. The behavioural models, inherently based on approximations, were then initially validated by comparing them with Actual Circuit behaviour, obtained using discrete components. These comparisons revealed that the models matched the Actual Circuit measurements. Finally, taking into account the conclusions of our theoretical study, an integrated version of this adaptive threshold spike detector was designed using 0.35-µm complementary metal–oxide–semiconductor technology. Simulations of this Circuit revealed that the proposed controller eliminated the static error and ensured efficient spike detection. Copyright © 2016 John Wiley & Sons, Ltd.

  • Theoretical study and optimisation of a standard deviation estimator Circuit for adaptive threshold spike detection
    International Journal of Circuit Theory and Applications, 2016
    Co-Authors: François Rummens, Stéphane Ygorra, Sylvie Renaud, Noëlle Lewis
    Abstract:

    This paper presents a theoretical study and the resulting architecture of an analogue-based standard deviation (SD) estimator, typically used in biomedical spike detectors to assess the noise level of bioelectrical recordings online. This well-known Circuit generated a significant inaccuracy, so the aim was to increase the efficiency of spike detection through proper calculation of the noise SD, by developing a rigorous, original theoretical study. The approach consisted of establishing behavioural models for the SD estimation Circuit to obtain a transfer function and compare different controllers. This modelling approach also highlighted the parameters available and the impact of their relationships on design optimisation. The behavioural models, inherently based on approximations, were then initially validated by comparing them with Actual Circuit behaviour, obtained using discrete components. These comparisons revealed that the models matched the Actual Circuit measurements. Finally, taking into account the conclusions of our theoretical study, an integrated version of this adaptive threshold spike detector was designed using 0.35-μm complementary metal–oxide–semiconductor technology. Simulations of this Circuit revealed that the proposed controller eliminated the static error and ensured efficient spike detection.

Mamoru Tanaka – One of the best experts on this subject based on the ideXlab platform.

S. Sundeep – One of the best experts on this subject based on the ideXlab platform.

  • An ANN Control of Maximum Power Point Tracking for Grid Connected Wind Machines
    International Review of Automatic Control (IREACO), 2014
    Co-Authors: S. Sundeep, G. Madhusudhana Rao, B. V. Sanker Ram
    Abstract:

    This research work investigates about the wind energy conversion system will receive the extensive attention among the various renewable energy systems. The extraction of the maximum possible power available wind energy is an important area of research among the speed sensorless MPPT control of wind area. This paper presents a power point tracking (MPPT) Technique for high performance wind turbine with induction machines based on expert systems (Artificial Neural Networks). In this paper, an ANN has been trained in off-line to learn about wind turbine characteristics of the torque with the wind speed and the speed of the machine which will be deployed in online for measuring the speed of the wind and torque. The reference speed of the machine is then calculated based on the control of the signal power feedback (PSF). Voltage oriented control of the machine is further integrated with an expert sensorless technique. The proposed method was simulated and conformed on the Actual Circuit in online