Bottom-up self-assembly nanofabrication process yields nanodevices with significantly more variations compared to the conventional top-down lithography used in CMOS fabrication. This is in addition to an increased def...
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ISBN:
(纸本)9781605588377
Bottom-up self-assembly nanofabrication process yields nanodevices with significantly more variations compared to the conventional top-down lithography used in CMOS fabrication. This is in addition to an increased defect density expected for self-assembled nanodevices. Therefore, it is one of the major design challenges to tolerate variation, in addition to defect tolerance, in emerging nano architectures. In this paper, we present a solution for variation tolerant logic mapping for FET based crossbar array nano architectures using Simulated Annealing. Furthermore, we extended the framework for defect tolerance. Experimental results including comparison with exact method confirm the effectiveness of the proposed approach.
In this paper, we derive a theoretical performance evaluation scheme of Kalman filter based channel tracking and data decoding for multiple-input multiple-output orthogonal frequency division multiplexed (MIMO-OFDM) c...
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ISBN:
(纸本)9781424442959
In this paper, we derive a theoretical performance evaluation scheme of Kalman filter based channel tracking and data decoding for multiple-input multiple-output orthogonal frequency division multiplexed (MIMO-OFDM) communication systems that are based on orthogonal space-time block codes. The derivation is approximate, however, it is novel and demonstrated accurate for practical scenarios. Assuming a prior distribution for the initial channel we have derived the instantaneous signal to interference and noise ratio (SINR) for consecutive transmission blocks in the absence of training by exploiting Kalman filtering to track the channel. A theoretical estimation of BER is then derived based on such instantaneous SINR values. The resulting analysis is able to study the effect of different parameters of the system such as the number of antennas, number of sub-carriers, mobile velocity and the assumed channel length on the BER performance of the system. Numerical examples confirm the validity of the theoretical analysis.
In this study, we present the conceptual design of a fully-passive transfemoral prosthesis. The proposed design is inspired by the analysis of the musculo-skeletal activity of the healthy human leg. In order to realiz...
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In this study, we present the conceptual design of a fully-passive transfemoral prosthesis. The proposed design is inspired by the analysis of the musculo-skeletal activity of the healthy human leg. In order to realize an energy efficient device, we introduce three storage elements, which are responsible of the energetic coupling between the knee and the ankle joints. Simulation results show that the power storage of the designed conceptual prosthesis is comparable with the human gait.
In this paper, a technique based on Independent Component Analysis (ICA) and morphological attribute filters is presented for the classification of high geometrical resolution hyperspectral images. The ICA is computed...
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Cognitive radio technology has been widely researched to improve the spectrum usage efficiency. Modeling of the spectrum occupancy in a cognitive framework including licensed and unlicensed users with various traffic ...
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ISBN:
(纸本)9781424455928;9781424455935
Cognitive radio technology has been widely researched to improve the spectrum usage efficiency. Modeling of the spectrum occupancy in a cognitive framework including licensed and unlicensed users with various traffic conditions, is a prior requirement to do the system analysis. In this paper, we develop a continuous-time Markov chain model to describe the radio spectrum usage, and derive the transition rate matrix for this model. In addition, we perform steady-state analysis to analytically derive the probability state vector. The proposed model and derived expressions are compared to the existing models, and examined through numerical analysis.
Two strategies for extraction of p-n junction's depletion capacitance compact model parameters are identified and compared by the present paper. Applying these in a numerical experiment and device measurements, it...
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Two strategies for extraction of p-n junction's depletion capacitance compact model parameters are identified and compared by the present paper. Applying these in a numerical experiment and device measurements, it is demonstrated that the reproducibility of the estimated parameter values can strongly depend on the extraction strategy applied within the nonlinear regression procedure. An approach to assess statistical properties of parameter extraction strategies is presented and the merits of such assessments are shown.
Hyperspectral imaging is a continuously growing area of remote sensing application. The wide spectral range, providing a very high spectral resolution, allows to detect and classify surfaces and chemical elements of t...
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Hyperspectral imaging is a continuously growing area of remote sensing application. The wide spectral range, providing a very high spectral resolution, allows to detect and classify surfaces and chemical elements of the observed image. The main problem of hyperspectral data is that the high spectral resolution is usually complementary to the spatial one, which can vary from a few to tens of meters. Many factors, such as imperfect imaging optics, atmospheric scattering, secondary illumination effects and sensor noise cause a degradation of the acquired image quality, making the spatial resolution one of the most expensive and hardest to improve in imaging systems. In this work, a novel method, based on the use of source separation technique and a spatial regularization step by simulated annealing is proposed to improve the spatial resolution of cover classification maps. Experiments have been carried out on both synthetic and real hyperspectral data and show the effectiveness of the proposed method.
High runtime failure rate as a result of reliability detractors is one of the major challenges for scaled-CMOS as well as emerging nanotechnologies. This results in multiple faults during life time operation. In this ...
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ISBN:
(纸本)9781424458349
High runtime failure rate as a result of reliability detractors is one of the major challenges for scaled-CMOS as well as emerging nanotechnologies. This results in multiple faults during life time operation. In this paper we propose a self-timed asynchronous architecture which can tolerate multiple transient bit-flips. This architecture has self-timed property, making it robust against delay variations caused by increased process variations at nanoscale. The proposed architecture can achieve 100% tolerance of single transient faults as well as more than 93% tolerance of multiple faults for failure rate less than 10 -2 .
Many software vendors are providing mechanisms for parallel content retrieval using multiple connections, e.g., parallel HTTP channels, to increase the availability and reliability of the download procedure. At the sa...
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Many software vendors are providing mechanisms for parallel content retrieval using multiple connections, e.g., parallel HTTP channels, to increase the availability and reliability of the download procedure. At the same time, there is no native verification mechanism to support simultaneous content verification from multiple sources. While it is possible to set-up multiple TLS tunnels with different sources, there is no guarantee that the data itself is authentic since the trust is placed on the connection and not in the data itself. In this paper we present a parallel verification mechanism based on hash trees, allowing clients to authenticate data segments regardless of the container from where they were retrieved from, but just with the original provider. Some benefits of the proposed mechanism include low CPU processing costs, low verification overhead and possibility to support legacy data.
In this paper, the use of Independent Component Discriminant Analysis (ICDA) for remote sensing classification is proposed. ICDA is a non-parametric method for discriminant analysis based on the application of a Bayes...
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In this paper, the use of Independent Component Discriminant Analysis (ICDA) for remote sensing classification is proposed. ICDA is a non-parametric method for discriminant analysis based on the application of a Bayesian classification rule on a signal composed by independent components. The method is based on the use of Independent Component Analysis (ICA) to choose a transform matrix so that the transformed components are as independent as possible. Then, a non parametric estimation of the density function is computed for each independent component. Finally, the Bayes rule is applied for classification assignment. The obtained results are compared with one of the most used classifier of hyperspectral images (Support Vector Machine) and show the comparative effectiveness of the proposed method.
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