The paper proposes a compression mechanism for multi-stage switching networks with multi-rate BPP (Binomial-Poisson-Pascal) traffic streams. The effectiveness of the proposed mechanism is compared to previously studie...
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The paper proposes a compression mechanism for multi-stage switching networks with multi-rate BPP (Binomial-Poisson-Pascal) traffic streams. The effectiveness of the proposed mechanism is compared to previously studied Call Admission Control (CAC) mechanisms for multi-rate switching networks, i.e. bandwidth reservation mechanism and threshold mechanism. The paper investigates by means of simulation method the influence of the CAC mechanisms on the key performance indicators of multi-service switching networks.
We have applied the generalized and universal distance measure NCD-Normalized compression Distance-to the problem of determining the types of file fragments via example. A corpus of files that can be redistributed to ...
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ISBN:
(纸本)9781424458790
We have applied the generalized and universal distance measure NCD-Normalized compression Distance-to the problem of determining the types of file fragments via example. A corpus of files that can be redistributed to other researchers in the field was developed and the NCD algorithm using k-nearest-neighbor as a classification algorithm was applied to a random selection of file fragments. The experiment covered circa 2000 fragments from 17 different file types. While the overall accuracy of the n-valued classification only improved the prior probability of the class from approximately 6% to circa 50% overall, the classifier reached accuracies of 85%-100% for the most successful file types.
To reduce the external memory cost, an efficient 5/3-DWT based embedded compression algorithm is proposed for H.264 decoder. Decoded frames are decomposed into 4×4 blocks which are then compressed into 32-bit or ...
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To reduce the external memory cost, an efficient 5/3-DWT based embedded compression algorithm is proposed for H.264 decoder. Decoded frames are decomposed into 4×4 blocks which are then compressed into 32-bit or 64-bit segments. The algorithm achieves compression ratio of 28~33% just with a slight quality degradation.
In this paper we propose a new method of test patterns compression based on a design of a dedicated SAT-based ATPG (Automatic Test Pattern Generator). This compression method is targeted to systems on chip (SoCs)provi...
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In this paper we propose a new method of test patterns compression based on a design of a dedicated SAT-based ATPG (Automatic Test Pattern Generator). This compression method is targeted to systems on chip (SoCs)provided with the P1500 test standard. The RESPIN architecture can be used for test patterns decompression. The main idea is based on finding the best overlap of test patterns during the test generation, unlike other methods, which are based on efficient overlapping of pre-generated test patterns. The proposed algorithm takes advantage of an implicit test representation as SAT problem instances. The results of test patterns compression obtained for standard ISCAS'85 and `89benchmark circuits are shown and compared with competitive test compression methods.
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive compression (NMPC), based on a novel combination of Bayesian Neural Networks (BNNs) and Hidden ...
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ISBN:
(纸本)9781424464258;9780769539942
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive compression (NMPC), based on a novel combination of Bayesian Neural Networks (BNNs) and Hidden Markov Models (HMM). The result is an interesting combination of properties: Linear processing time, constant memory storage performance and great adaptability to parallelism. Though not limited for such uses, when used for online compression (compressing streaming inputs without the latency of collecting blocks) it often produces superior results compared to other algorithms for this purpose. It is also a natural algorithm to be implemented on parallel platforms such as FPGA chips.
Motivated by the Markov chain Monte Carlo (MCMC) relaxation method of Jalali and Weissman, we propose a lossy compression algorithm for continuous amplitude sources that relies on a finite reproduction alphabet that g...
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ISBN:
(纸本)9781424464258
Motivated by the Markov chain Monte Carlo (MCMC) relaxation method of Jalali and Weissman, we propose a lossy compression algorithm for continuous amplitude sources that relies on a finite reproduction alphabet that grows with the input length. Our algorithm asymptotically achieves the optimum rate distortion (RD) function universally for stationary ergodic continuous amplitude sources. However, the large alphabet slows down the convergence to the RD function, and is thus an impediment in practice. We thus propose an MCMC-based algorithm that uses a (smaller) adaptive reproduction alphabet. In addition to computational advantages, the reduced alphabet accelerates convergence to the RD function, and is thus more suitable in practice.
Reducing the number of transmitted bytes in a wireless sensor network reduces the time the radio is on, resulting in a significant increase in battery lifetime. Toward this end we have developed a compression techniqu...
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Reducing the number of transmitted bytes in a wireless sensor network reduces the time the radio is on, resulting in a significant increase in battery lifetime. Toward this end we have developed a compression technique that is independent of the protocols used in the network, acts as a transparent layer, and consumes minimal computing resources. Patterns in recent packets are identified and replaced in the transmitted packet by bit flags. This algorithm was tested on packet traces collected from commercial wireless sensor networks for 40-80% compression, yielding comparable energy savings in a time-synchronized network.
In this paper we propose an x-coordinate point compression method for elliptic curves over F p , where p >; 3 is prime, as an alternative to the classical y-coordinate point compression method. A point P̃ = (x̃, y)...
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In this paper we propose an x-coordinate point compression method for elliptic curves over F p , where p >; 3 is prime, as an alternative to the classical y-coordinate point compression method. A point P̃ = (x̃, y) will be compressed as P = (x, y) where x has only two bits and, thus, our method allows more compact representations when [log 2 x] >; [log 2 y]+1. Both our compression and decompression algorithms involve solving cubic equations or, in some cases, only computing cube roots modulo a prime, thus being of worst-case complexity O((log 2 p) 4 ). For some particular cases, our compression algorithm can be significantly improved, requiring only two multiplications (thus, being of worst-case complexity O((log 2 p) 2 )).
In data compression or source coding algorithms, input sequences of symbols are converted to shorter sequences while the original information remains unchanged. One of the well-known data compression algorithms is Def...
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ISBN:
(纸本)9781424467600
In data compression or source coding algorithms, input sequences of symbols are converted to shorter sequences while the original information remains unchanged. One of the well-known data compression algorithms is Deflate which is designed based on the LZ method. Deflate method has three different modes where its second mode is applicable for real-time applications. In this mode, a certain static table of Huffman codes is employed during the coding procedure. In this paper, a new version of deflate algorithm is proposed and implemented in hardware. In the proposed method, a new basic coding table is employed. This table is modified adaptively based on the input sequence. Simulation results show that in this adaptive algorithm, the coding performance is improved. In the hardware implementation of the new method, through some parallelism concepts, we try to improve the hardware utilization and throughput.
Medical imaging is crucial for early detection and diagnosis of illnesses. The increasing amount of high resolution scans being done every day requires efficient compression algorithms. A magnetic resonance image (MRI...
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ISBN:
(纸本)9781424464258;9780769539942
Medical imaging is crucial for early detection and diagnosis of illnesses. The increasing amount of high resolution scans being done every day requires efficient compression algorithms. A magnetic resonance image (MRI) consists of a series of many cuts or slices. Viewed as a 3D image, it contains a 3D figure surrounded by background. This background is not clinically relevant.
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