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Author

B. Chatterjee

Other affiliations: Texas Instruments
Bio: B. Chatterjee is an academic researcher from University of Engineering & Management. The author has contributed to research in topics: Magnetic field & Quantum well. The author has an hindex of 5, co-authored 27 publications receiving 95 citations. Previous affiliations of B. Chatterjee include Texas Instruments.

Papers
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Proceedings ArticleDOI
13 Dec 2004
TL;DR: Key features of a low cost technology option for mobile products (MP) and a high performance technology option (HP) for DSP based applications are described.
Abstract: This paper presents a 65 nm CMOS technology that achieves a logic density of 900 k-gates/mm/sup 2/ and a SRAM memory density of 1.4 Mb/mm/sup 2/ using a sub-0.49 /spl mu/m/sup 2/ bitcell. Key features of a low cost technology option for mobile products (MP) and a high performance technology option (HP) for DSP based applications are described.

24 citations

Journal ArticleDOI
TL;DR: Researchers have selected a useful, timesaving model to find an image as melanoma or even naevus, which achieves a favorable accuracy of 96.8% with few noticeable epochs which concern other 12 machine learning models and five deep learning models.
Abstract: Machines can acknowledge the images of skin lesion as well as the disease compared to an experienced dermatologist. These might be executed by giving a proper label for the provided images of skin lesion. Within the proposed study researchers have examined various frameworks for detection of skin cancer as well as classification of melanoma. The current research includes a unique image pre-processing technique and modification of the image followed by image segmentation. The 23 texture and ten shape features of the dataset are further refined with feature engineering techniques. The improved dataset has been processed inside a Deep Neural Network models by binary cross-entropy. The dataset passes through several mixes of multiple activation layers with varying features and optimization techniques. As an outcome of the study, researchers have selected a useful, timesaving model to find an image as melanoma or even naevus. The model was evaluated with 170 images of MED NODE and 2000 images of ISIC dataset. This improved framework achieves a favorable accuracy of 96.8% with few noticeable epochs which concern other 12 machine learning models and five deep learning models. In the future, certainly there can be an investigation with several classes of skin cancer with an improved dataset.

17 citations

Book ChapterDOI
01 Jan 2019
TL;DR: A detailed study has been carried out for a few applications in detecting brain diseases by EEG andMRI and a detail comparison study is made between EEG and MRI.
Abstract: Encephalogram (EEG) provides the recordings of the brain and is used for detecting the brain diseases In this paper, a detailed study has been carried out for a few applications in detecting brain diseases by EEG and MRI In addition, a detail comparison study is made between EEG and MRI This paper has been arranged in two phases out of which, in the first phase, a detailed study has been carried out for EEG processing The next phase consists of a comparison study of the detection of brain diseases by both EEG and MRI

10 citations

Journal ArticleDOI
TL;DR: It appears that the EEM increases with decreasing film thickness, increasing electric field and increases with increasing surface electron concentration exhibiting spikey oscillations because of the crossing over of the Fermi level by the quantized level in quantum wells.
Abstract: In this paper we study the influence of strong electric field on the two dimensional (2D)effective electron mass (EEM) at the Fermi level in quantum wells of III-V, ternary and quaternary semiconductors within the framework of k x p formalism by formulating a new 2D electron energy spectrum. It appears taking quantum wells of InSb, InAs, Hg(1-x)Cd(x)Te and In(1-x)Ga(x)As(1-y)P(y) lattice matched to InP as examples that the EEM increases with decreasing film thickness, increasing electric field and increases with increasing surface electron concentration exhibiting spikey oscillations because of the crossing over of the Fermi level by the quantized level in quantum wells and the quantized oscillation occurs when the Fermi energy touches the sub-band energy. The electric field makes the mass quantum number dependent and the oscillatory mass introduces quantum number dependent mass anisotropy in addition to energy. The EEM increases with decreasing alloy composition where the variations are totally band structure dependent. Under certain limiting conditions all the results for all the cases get simplified into the well-known parabolic energy bands and thus confirming the compatibility test. The content of this paper finds three applications in the fields of nano-science and technology.

6 citations


Cited by
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Journal ArticleDOI
01 Oct 1980

1,565 citations

Proceedings ArticleDOI
28 Jun 2006
TL;DR: It is demonstrated that the introduction of a second parallel network can increase performance while improving efficiency, and different strategies for distributing traffic over the subnetworks are evaluated.
Abstract: We develop detailed area and energy models for on-chip interconnection networks and describe tradeoffs in the design of efficient networks for tiled chip multiprocessors. Using these detailed models we investigate how aspects of the network architecture including topology, channel width, routing strategy, and buffer size affect performance and impact area and energy efficiency. We simulate the performance of a variety of on-chip networks designed for tiled chip multiprocessors implemented in an advanced VLSI process and compare area and energy efficiencies estimated from our models. We demonstrate that the introduction of a second parallel network can increase performance while improving efficiency, and evaluate different strategies for distributing traffic over the subnetworks. Drawing on insights from our analysis, we present a concentrated mesh topology with replicated subnetworks and express channels which provides a 24% improvement in area efficiency and a 48% improvement in energy efficiency over other networks evaluated in this study.

547 citations

Book ChapterDOI
30 Aug 2009
TL;DR: The techniques used for system-level analysis, both hardware and software; circuit extraction, taking the chip down to the transistor level, and working back up through the interconnects to create schematics; and process analysis, looking at how a chip is made, and what it is made of are discussed.
Abstract: This paper gives an overview of the place of reverse engineering (RE) in the semiconductor industry, and the techniques used to obtain information from semiconductor products. The continuous drive of Moore's law to increase the integration level of silicon chips has presented major challenges to the reverse engineer, obsolescing simple teardowns, and demanding the adoption of new and more sophisticated technology to analyse chips. Hardware encryption embedded in chips adds a whole other level of difficulty to IC analysis. This paper covers product teardowns, and discusses the techniques used for system-level analysis, both hardware and software; circuit extraction, taking the chip down to the transistor level, and working back up through the interconnects to create schematics; and process analysis, looking at how a chip is made, and what it is made of. Examples are also given of each type of RE. The paper concludes with a case study of the analysis of an IC with embedded encryption hardware.

341 citations

Journal ArticleDOI
TL;DR: A unified approach that directly predicts the change of key transistor parameters under various process and design conditions for both NBTI and CHC effects is presented, and it is demonstrated that the proposed method very well predicts the degradation.
Abstract: Negative bias temperature instability (NBTI) and channel hot carrier (CHC) are the leading reliability concerns for nanoscale transistors. The de facto modeling method to analyze CHC is based on substrate current Isub, which becomes increasingly problematic with technology scaling as various leakage components dominate Isub. In this paper, we present a unified approach that directly predicts the change of key transistor parameters under various process and design conditions for both NBTI and CHC effects. Using the general reaction-diffusion model and the concept of surface potential, the proposed method continuously captures the performance degradation across subthreshold and strong inversion regions. Models are comprehensively verified with an industrial 65-nm technology. By benchmarking the prediction of circuit performance degradation with the measured ring oscillator data and simulations of an amplifier, we demonstrate that the proposed method very well predicts the degradation. For 65-nm technology, NBTI is the dominant reliability concern, and the impact of CHC on circuit performance is relatively small.

333 citations