The simple and complete asymptotical analysis is given for a uniform polar quantizer with respect to mean-square error (MSE). Also, an algorithm for constructing an optimal uniform quantizer for small and moderate N i...
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The simple and complete asymptotical analysis is given for a uniform polar quantizer with respect to mean-square error (MSE). Also, an algorithm for constructing an optimal uniform quantizer for small and moderate N is shown. The algorithm is demonstrated on the Gaussian source example. We also give the conditions for optimality of the polar quantizer and all main equations for phase partitions and optimal number of levels are presented.
This study presents a new multiple description coding method based on a three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm in WiMAX for videos. Applying a poly-phase sampling technique to s...
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This study presents a new multiple description coding method based on a three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm in WiMAX for videos. Applying a poly-phase sampling technique to sample an input video over its intra-frame or inter-frame, several independent and highly correlated descriptions are generated. Then, a 3-D SPIHT algorithm is applied to each of the produced descriptions. Finally, the coding results are transmitted via different channels. This proposed approach achieves high compression ratio, enhances transmission speed, and more importantly, attains acceptable video quality when channel congestion occurs. Experimental results are provided to demonstrate promising performance of the proposed method.
Lots of clustering algorithms have been developed, and in most of them some parameters should be determined by hand. However, it is very difficult to determine them manually without any prior domain knowledge. To solv...
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Lots of clustering algorithms have been developed, and in most of them some parameters should be determined by hand. However, it is very difficult to determine them manually without any prior domain knowledge. To solve this problem, a novel similarity based clustering algorithm was presented. It aimed at avoiding instructional parameters to be determined by hand, and at the same time, improving the efficiency of clustering. By introducing fuzzy adaptive resonance theory (ART) to pre-train the similarity criterion, the instructional parameter was determined dynamically. The new clustering algorithm was analyzed and applied later to cluster the product data. A comparison with K-means shows that this algorithm produced clusters with higher quality and in less time. Validity analysis to the clustering results confirms applicability of this algorithm
In the sort-last-sparse parallel volume rendering system on distributed memory multicomputers, as the number of processors increases, in the rendering phase, we can get a good speedup because each processor renders im...
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ISBN:
(纸本)0769503500
In the sort-last-sparse parallel volume rendering system on distributed memory multicomputers, as the number of processors increases, in the rendering phase, we can get a good speedup because each processor renders images locally without communicating with other processors. However, in the compositing phase, a processor has to exchange local images with other processors. When the number of processors is over a threshold, the image compositing time becomes a bottleneck. In this paper, we proposed three compositing methods, the binary-swap with bounding rectangle method, the binary-swap with run-length encoding and static load-balancing method, and the binary-swap with bounding rectangle and run-length encoding method, to efficiently reduce the compositing time in the sort-last-sparse parallel volume rendering system on distributed memory multicomputers. The proposed methods were implemented on an SP2 parallel machine along with the binary-swap compositing method. The experimental results show that the binary-swap with bounding rectangle and run-length encoding method has the best performance among the four methods.
Under the architecture of Networking Systems of AI (NSAI), we propose a three-tier edge computing platform called Open Service for NSAI (OpenSAI), which can jointly configure the application execution and compute-stor...
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ISBN:
(数字)9798350373011
ISBN:
(纸本)9798350373028
Under the architecture of Networking Systems of AI (NSAI), we propose a three-tier edge computing platform called Open Service for NSAI (OpenSAI), which can jointly configure the application execution and compute-storage-network resources, for online application-network adaption, to ensure the efficiency and reliability of the services. In this research, we investigate a specific task-device adaptation optimization problem in OpenSAI, which recommend application tasks to distributed computing devices. We evaluate the performance of various optimization and search algorithms in recommending optimal task-device combinations, which show significant differences among the algorithms in terms of recommendation runtime costs and task adaptability. Overall, the hybrid recommendation of SCORE Algorithm, Particle Swarm Optimization, and Item-Item Collaborative Filtering demonstrates the best performance in both time efficiency and fitness scores across multiple scenarios.
The transmission of still images over wireless channels is an exercise in tradeoffs. For bandwidth efficiency, a high source compression rate is required. However, the transmission must be robust towards channel error...
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The transmission of still images over wireless channels is an exercise in tradeoffs. For bandwidth efficiency, a high source compression rate is required. However, the transmission must be robust towards channel errors since wireless channels are subject to fading. These are conflicting requirements. High source compression rates result in images that are very vulnerable to any single bit error. Low-rate channel coding to protect highly compressed images from channel errors drastically reduces the bandwidth efficiency. The combinations of set partitioning in hierarchical trees (SPIHT) wavelet based source coding and list Viterbi (1971) algorithm (LVA) for channel decoding allows for bandwidth efficient, error resilient image transmission over wireless channels. SPIHT offers compression superior to existing DCT and fractal based algorithms. LVA decoding outperforms conventional Viterbi decoding at the expense of an increase in complexity. We construct a system model to transmit raw images over AWGN and narrowband Rayleigh fading channels with SPIHT source coding and LVA decoding using rate compatible punctured convolutional (RCPC) codes. We also propose a method of unequal error protection over the channel. We show that this scheme is superior to equal error protection under the premise that there is a minimum acceptable level of image quality below which the received image has no utility.
In several public-key cryptosystems, the main operation consists of the modular exponentiation, which is performed using successive modular multiplications. The size of the operands that are used in these cryptosystem...
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In several public-key cryptosystems, the main operation consists of the modular exponentiation, which is performed using successive modular multiplications. The size of the operands that are used in these cryptosystems is considerably large (1024 bits), consuming a considerable amount of time. This impacts on the performance of the cryptosystem, especially in real time applications. In order to reduce the execution time in these cryptosystems, the total number of modular multiplications must be reduced. There are several methods that attempt to reduce this number either by partitioning the exponent in windows or by reducing the number of elements to be multiplied. In this paper, we propose a fast and compact reconfigurable hardware for computing modular exponentiation using the addition-chain methods.
This paper put forward a semantic-based video analytic approach and it's two algorithms in the Wushu video retrieval. Firstly, it can be taken a edge detection to the special-temporal slices by using the edge dete...
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This paper put forward a semantic-based video analytic approach and it's two algorithms in the Wushu video retrieval. Firstly, it can be taken a edge detection to the special-temporal slices by using the edge detection operator based on bilateral filtering, and then extracting and training the classes used the key frame semantic based on SVM. The system which is completed by the two algorithms implement the segmentation and retrieval of the Wushu video. The experiment show that it is better to retrieval according to the characters of the Wushu video by using this system.
Conventional programmable shifters consume considerable amount of power and dominates the overall complexity of the entire circuit in some applications. Such power and area overhead become redundant when only part of ...
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Conventional programmable shifters consume considerable amount of power and dominates the overall complexity of the entire circuit in some applications. Such power and area overhead become redundant when only part of the shifting amount is required. In this paper, therefore, a new design of partial programmable shifters is proposed to reduce the complexity and power consumption, by adopting integer partition technique to dynamically generate the simplest numerical combination of all the required shifting amounts. Such design algorithm has been validated by using 8-bit programmable shifters benchmarks. The synthesis results show that the proposed design reduces the logic complexity and dynamic power by up to 62.6% and 45.7% over the conventional full programmable shifters.
Today, event logging is a widely accepted concept with a number of event formatting standards and event collection protocols. Event logs contain valuable information not only about system faults and performance issues...
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ISBN:
(纸本)9781509037827
Today, event logging is a widely accepted concept with a number of event formatting standards and event collection protocols. Event logs contain valuable information not only about system faults and performance issues, but also about security incidents. Unfortunately, since modern data centers and computer networks are known to produce large volumes of log data, the manual review of collected data is beyond human capabilities. For automating this task, a number of data mining algorithms and tools have been suggested in recent research papers. In this paper, we will describe the application of the LogCluster tool for mining event patterns and anomalous events from security and system logs.
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