In this paper, we present a simplified design, characteristic performance evaluation and comparative analysis for a Carbon Nanotube-based Operational Amplifier (CNT-OPAMP), using a circuit-compatible compact model for...
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In this paper, we present a simplified design, characteristic performance evaluation and comparative analysis for a Carbon Nanotube-based Operational Amplifier (CNT-OPAMP), using a circuit-compatible compact model for the intrinsic channel region of the MOSFET-like single-walled Carbon Nanotube Field-Effect Transistors (CNFETs). the study makes a simulation-based assessment on the design and performance analysis of a CNFET-based CMOS-OPAMP and compares the result to that of the conventional Silicon-based OPAMP for 32nm technology. the comparative analysis from our study shows a promising increase in operation Bandwidth by 33.8% and in Gain-Bandwidth product (GBP) by 105.7% for the CNFET-OPAMP, with a switching speed faster by over 200% and a huge reduction in power consumption by over 600 times. It also shows a considerably good noise performance with an increment of CMRR by a factor of two. the results obtained in our study suggest that the CNT-OPAMP has a promising potential for low-power high-speed applications in nanoelectronic circuits.
We present the design of a very low power and high throughput Advanced Encryption Standard (AES) processor. A sophisticated AES algorithm without sacrificing its security features, throughput and area is used to desig...
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We present the design of a very low power and high throughput Advanced Encryption Standard (AES) processor. A sophisticated AES algorithm without sacrificing its security features, throughput and area is used to designthe processor. Due to the optimization of the algorithm and a number of design considerations, the processor shows its superiority over other AES processors. the proposed processor is simulated on the FPGA platform and Quartus II development software of Altera device of family Stratix II GX is used to simulate the design. A Power Play Early Power Estimation Tool is used to approximate the power consumption of the proposed processor. Later on the more reliable power analysis tool named Power Play Power Analyzer is used to estimate the static and dynamic power dissipation in the Processor. the high level of system integration along with very low power consumption and high throughput makes the AES processor an ideal choice for a range of application including small computing devices, smart card readers and network applications like WLAN, WPAN, WSN etc.
the paradigm of RIA (Rich Internet Application) emerged since users' tendency to use web applications was changed for the sake of convenience, and the Flex was presented as a platform to develop the RIA withthe a...
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the paradigm of RIA (Rich Internet Application) emerged since users' tendency to use web applications was changed for the sake of convenience, and the Flex was presented as a platform to develop the RIA withthe advantage of prevalance by the Adobe. the Flex is mainly composed of configuring user screens, which has insufficient compatibility and maintenance due to its unified layer. Accordingly, this paper would design and implement a FMT (Flex Mlti-Tier) framework to improve compatibility and maintenance of the Flex.
＜正＞the paper gradually discusses how to use the potential of combining the visual graphic design and research learning mode to develop graphic comments polysemy of poster and future to develop poster design ability...
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＜正＞the paper gradually discusses how to use the potential of combining the visual graphic design and research learning mode to develop graphic comments polysemy of poster and future to develop poster design ability by proposing issues such as why accurate full of images designed,issue analysis-factors may influence create thingking ability development,solutions- how to create graphic designthinking *** most important issue to connect three keywords of "visual potential"、"Characteristics of visual experience thinking"and "design" is to improve graphic *** the key to develop creative simple graphics can show rich in content,then all viewers will have a wealth of associations around the *** comprehensive analysis of the ideographic graphics,original graphics,graphic aesthetic, simple graphics,graphics layout and graphics of the symbolic links and other relevant factors,in particular,to improve the graphical impact,the proposed new perspective.
Symbolic methods in computer-aided verification rely heavily on constraint solvers. the correctness and reliability of these solvers are of vital importance in the analysis of safety-critical systems, e.g., in the aut...
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Symbolic methods in computer-aided verification rely heavily on constraint solvers. the correctness and reliability of these solvers are of vital importance in the analysis of safety-critical systems, e.g., in the automotive context. Satisfiability results of a solver can usually be checked by probing the computed solution. this is in general not the case for un-satisfiability results. In this paper, we propose a certification method for unsatisfiability results for mixed Boolean and non-linear arithmetic constraint formulae. Such formulae arise in the analysis of hybrid discrete/continuous systems. Furthermore, we test our approach by enhancing the iSAT constraint solver to generate unsatisfiability proofs, and implemented a tool that can efficiently validate such proofs. Finally, some experimental results showing the effectiveness of our techniques are given.
Recommender systems help users find their items of interest from large data collections with little effort. Collaborative filtering (CF) is one of the most popular approaches for making recommendations. While signific...
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ISBN:
(纸本)9781450305280
Recommender systems help users find their items of interest from large data collections with little effort. Collaborative filtering (CF) is one of the most popular approaches for making recommendations. While significant work has been done on improving accuracy of CF methods, some of the most popular CF approaches are limited in terms of scalability and efficiency. the size of data in modern recommender systems is growing rapidly in terms of both new users and items and new ratings. Item-based recommendation is one of the CF approaches used widely in practice. It computes and uses an item-item similarity matrix in order to predict unknown ratings. Previous works on item-based CF method confirm its usefulness in providing high quality top-fc results. In this paper, we design a scalable algorithm for top-fc recommendations using this method. We achieve this by probabilistic modeling of the similarity matrix. A unique challenge here is that the ratings that are aggregated to produce the aggregate predicted score for a user should be obtained from different lists for different candidate items and the aggregate function is non-monotone. We propose a layered architecture for CF systems that facilitates computation of the most relevant items for a given user. We design efficient top-fc algorithms and data structures in order to achieve high scalability. Our algorithm is based on abstracting the key computation of a CF algorithm in terms of two operations - probe and explore. the algorithm uses a cost-based optimization whereby we express the overall cost as a function of a similarity threshold and determine its optimal value for minimizing the cost. We empirically evaluate our theoretical results on a large real world dataset. Our experiments show our exact top-k algorithm achieves better scalability compared to solid baseline algorithms.
Traditional error-correcting output codes (ECOCs) decompose a multi-class classification problem into many binary problems. Although it seems natural to use ECOCs for multi-label problems as well, doing so naively cre...
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Traditional error-correcting output codes (ECOCs) decompose a multi-class classification problem into many binary problems. Although it seems natural to use ECOCs for multi-label problems as well, doing so naively creates issues related to: the validity of the encoding, the efficiency of the decoding, the predictability of the generated codeword, and the exploitation of the label dependency. Using canonical correlation analysis, we propose an error-correcting code for multi-label classification. Label dependency is characterized as the most predictable directions in the label space, which are extracted as canonical output variates and encoded into the codeword. Predictions for the codeword define a graphical model of labels with both Bernoulli potentials (from classifiers on the labels) and Gaussian potentials (from regression on the canonical output variates). Decoding is performed by mean-field approximation. We establish connections between the proposed code and research areas such as compressed sensing and ensemble learning. Some of these connections contribute to better understanding of the new code, and others lead to practical improvements in code design. In our empirical study, the proposed code leads to substantial improvements compared to various competitors in music emotion classification and outdoor scene recognition. Copyright 2011 by the authors.
Non-Negative Matrix Factorization (NMF) is a dimensionality reduction method that has been shown to be very useful for a variety of tasks in machine learning and data mining. One of the fastest algorithms for NMF is t...
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Non-Negative Matrix Factorization (NMF) is a dimensionality reduction method that has been shown to be very useful for a variety of tasks in machine learning and data mining. One of the fastest algorithms for NMF is the Block Principal Pivoting method (BPP) of (Kim & Park, 2008b), which follows a block coordinate descent approach. the optimization in each iteration involves solving a large number of expensive least squares problems. Taking the view that the design matrix was generated by a stochastic process, and using the asymptotic normality of the least squares estimator, we propose a method for improving the performance of the BPP method. Our method starts with a small subset of the columns and rows of the original matrix and uses frequentist hypothesis tests to adaptively increase the size of the problem. this achieves two objectives: 1) during the initial phase of the algorithm we solve far fewer, much smaller sized least squares problems and 2) all hypothesis tests failing while using all the data represents a principled, automatic stopping criterion. Experiments on three real world datasets show that our algorithm significantly improves the performance of the original BPP algorithm. Copyright 2011 by the authors.
Reduction of structural complexity of digital systems has been emerging as one of the major areas of concern to the system designers. the deployment of any physical circuit or system in any specific application is sol...
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Reduction of structural complexity of digital systems has been emerging as one of the major areas of concern to the system designers. the deployment of any physical circuit or system in any specific application is solely determined by the intricacy of the concerned circuit which restricts the use of sophisticated circuits in high speed operation. thus the design of computationally efficient structure has drawn special attention to the modern researchers. Due to the immense development of evolutionary computation techniques over the last few years, they are being increasingly used for a number of signal processing applications. this paper deals with one such robust technique called Differential Evolution (DE) and the impact of its different mutation strategies for efficient design of multiplier-less low-pass Finite duration Impulse Response (FIR) filter. In order to find out the most favourable mutation scheme, the computational efficiency of various mutation schemes has been studied. For this purpose, the convergence behaviour and error histogram of DE algorithm has been presented. From the simulation results, the name of the computationally most efficient mutation strategy has been suggested. Finally, the superiority of the established mutation strategy has been reconfirmed in terms of the filter performance.
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