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检索条件"主题词=Compression algorithms"

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Dynamic data compression for wireless transmission over a fading channel

Dynamic data compression for wireless transmission over a fa...

引用

Annual Conference on Information Sciences and Systems (CISS)

作者： Michael J. Neely University of Southern California USA

We consider a wireless node that randomly receives data from different sensor units. The arriving data must be compressed, stored, and transmitted over a wireless link, where both the compression and transmission operations consume power. Specifically, the controller must choose from one of multiple compression options every timeslot. Each option requires a different amount of power and has different compression ratio properties. Further, the wireless link has potentially time-varying channels, and transmission rates depend on current channel states and transmission power allocations. We design a dynamic algorithm for joint compression and transmission, and prove that it comes arbitrarily close to minimizing average power expenditure, with an explicit tradeoff in average delay. The algorithm is simple to implement and does not require knowledge of probability distributions for packet arrivals or channel states.

关键词： Data compression Fading Wireless sensor networks Signal processing algorithms Algorithm design and analysis Delay compression algorithms Energy efficiency Stochastic processes Scheduling algorithm

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Adaptive Filesystem compression for Embedded Systems 08

Adaptive Filesystem Compression for Embedded Systems

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2008 Design, Automation and Test in Europe (DATE 2008), vol.3

作者： Lan S. Bai Haris Lekatsas Robert P. Dick Northwestern University Evanston IL Vorras Corporation Princeton NJ

ISBN: (纸本)9783981080131

Embedded system secondary storage size is often constrained, yet storage demands are growing as a result of increasing application complexity and storage of personal data and multimedia files. Filesystem compression offers a solution. This paper formalizes the problem of automatic filesystem compression using multiple compression algorithms. The average latency of on-line file accesses is optimized under a constraint on filesystem capacity. Our solution is based on predictive control. Predicted latency implications are used to solve the file compression state selection problem using a multiple choice knapsack problem formulation. This approach is evaluated on filesystem traces and compared with other efficient heuristics. Our approach results in 34.1% reduction in file access latency compared to a straight-forward heuristic that decompresses frequently-accessed files and compresses least recently used files with more aggressive compression algorithms. It reduces file access latency by 67.7% compared to uniformly compressing files to the shallowest level required to meet storage capacity constraints.

关键词： File systems Embedded systems compression algorithms program complexity personal data STORAGE(BY SIZE) Latency MULTI-MEDIA SYSTEM

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An effective wavelet-based lossy compression of noisy ECG signals

An effective wavelet-based lossy compression of noisy ECG si...

引用

IEEE Region 10 International Conference TENCON

作者： M. Sabarimalai Manikandan S. Dandapat Department of Electronics and Communication Engineering Indian Institute of Technology Guwahati Assam India

Noise degrades the rate-distortion performance of any electrocardiogram (ECG) compression algorithm. In distortion driven lossy coding approach, the bit stream is truncated at the bit rate that corresponds to a guaranteed user defined distortion level measured using the percentage root mean square difference (PRD). In many lossy compression methods, noise filtering may be implicitly done when performing the thresholding or/and quantization. In such a case, noise decreases the compression ratio for the specified distortion level. In this paper, we propose an effective wavelet-based lossy compression of noisy ECG signals based on the set partitioning in hierarchical trees (SPIHT) coding algorithm and novel wavelet energy based weighted PRDs (WEWPRDs) criterion. The PRDs measures normalized root mean squared difference between wavelet subband coefficients of the original and compressed signals. The dynamic weights based on wavelet energy feature represent the actual contribution of the subbands that are used to discriminate different frequency subbands, particularly subbands corresponding to noise. The WEWPRDs criterion appears to be a correct representation of the amount of signal distortion at all subbands and robust to insignificant errors in some bands. Thus, this criterion leads to a better measure of the rate-distortion (R-D) performance of the coder. Experiments on several noisy records from the widely used MIT-BIH arrhythmia (mita) database show that the proposed scheme outperforms PRD and wavelet based weighted PRD (WWPRD) measurement criteria based schemes.

关键词： Electrocardiography Distortion measurement Rate-distortion Degradation compression algorithms Bit rate Loss measurement Root mean square Filtering Quantization

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Architecture of a Low Storage Digital Pixel Sensor Array with an On-Line Block-Based compression

Architecture of a Low Storage Digital Pixel Sensor Array wit...

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IEEE International Workshop on Electronic Design, Test and Applications (DELTA)

作者： Milin Zhang Amine Bermak Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong China

In this paper, a block-based architecture of digital pixel sensor (DPS) array integrated with an on-line compression algorithm is proposed. The proposed technique is based on a block divided storage and compression scheme of the original image. Image capture, storage, and reordering are completed simultaneously and performed on-line while storing pixel value into the on-chip memory array. More than 60% of memory saving is achieved using the proposed block-based design. Furthermore, block-based design greatly reduces the accumulation error inherent in DPCM type of processing. Simulation results show that the PSNR result can reach around 30 dB with a compression ratio of less than 3 BPP.

关键词： Sensor arrays Pulse width modulation Space vector pulse width modulation Time domain analysis Image storage Image coding Biosensors compression algorithms Voltage Counting circuits

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Design of multi-mode depth buffer compression for 3D graphics system

Design of multi-mode depth buffer compression for 3D graphic...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Tzung-Rung Jung Lan-Da Van Teng-Yao Sheu Cheng-Wei Lin Wai-Chi Fang Department of Computer Science National Chiao Tung University Hsinchu Taiwan TSMC Distinguished Chair Professor Department of Electronics Engineering National Chiao Tung University Hsinchu Taiwan

An innovative multi-mode depth buffer compression algorithm has been developed for 3D graphics system. It adaptively compresses the depth buffer data according to different scene changes by employing 19 compression modes generated from three compression algorithms including DDPCM, HA, and general DDPCM. Furthermore, this novel algorithm supports one-plane and two-plane compression modes and manipulates break points more efficiently. For 8x8 tile size and 16-bit depth values, the proposed multi-mode algorithm can achieve 1.91:1 compression ratio on average and improve 76.9% and 39.4% compared with the HA and the DDPCM compression methods, respectively. The modified efficient depth buffer compression can achieve 10.56:1 and 7.76:1 compression ratio in one-plane mode and two-plane mode, respectively. The modified DDPCM can achieve 6.48:1 and 5.39:1 compression ratio in one-plane mode and two-plane mode, respectively.

关键词： Tiles compression algorithms Three dimensional displays Algorithm design and analysis Pixel Graphics Patents

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Anomaly-Based Hyperspectral Image compression

Anomaly-Based Hyperspectral Image Compression

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Qian Du Wei Zhu James E. Fowler Department of Electrical and Computer Engineering GeoResources Institute Mississippi State University USA

We propose a new lossy compression algorithm for hyperspectral images, which is based on spectral principal component analysis (PCA), followed by JPEG2000 (JP2K). The approach employs an anomaly-removal model in the compression process to preserve anomalous pixels. Results on two different hyperspectral image scenes show that the new algorithm not only provides good post-compression anomaly-detection performance but also improves rate-distortion performance.

关键词： Hyperspectral imaging Image coding Principal component analysis Discrete wavelet transforms compression algorithms Transform coding Pixel Rate-distortion Decorrelation Personal communication networks

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Efficient Sensor Network Reprogramming through compression of Executable Modules

Efficient Sensor Network Reprogramming through Compression o...

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： Nicolas Tsiftes Adam Dunkels Thiemo Voigt Swedish Institute of Computer Science Sweden

Software in deployed sensor networks needs to be updated to introduce new functionality or to fix bugs. Reducing dissemination time is important because the dissemination disturbs the regular operation of the network. We present a method for reducing the dissemination time and energy consumption based on compression of native code modules. Code compression reduces the size of the software update, but the decompression on the sensor nodes requires processing time and energy. We quantify these trade-offs for seven different compression algorithms. Our results show that GZIP has the most favorable trade-offs, saving on average 67% of the dissemination time and 69% of the energy in a multi-hop wireless sensor network.

关键词： Energy consumption Decoding Data compression compression algorithms Computer bugs Spread spectrum communication Computer science Wireless sensor networks Embedded software Application software

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Improving the k-svd facial image compression using a linear deblocking method

Improving the k-svd facial image compression using a linear ...

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IEEE Convention of the Electrical and ELectronic Engineers in Israel

作者： Ori Bryt Michael Elad The Electrical Engineering Department Technion-Israel Institute of Technology Israel The Computer Science Department Technion-Israel Institute of Technology Israel

The use of sparse representations in signal processing is gradually increasing in the past several years. In a previous work we proposed a new method for compressing facial images using the K-SVD algorithm, which is a novel algorithm for training overcomplete dictionaries that lead to sparse signal representations. This method was shown to be most efficient, surpassing the JPEG2000 performance significantly. In this paper we present a significant addition to our compression algorithm in the form of image deblocking. Since the encoding is done in patches, a visually disturbing artifacts of blockiness appear in the reconstructed images. We eliminate these artifacts using a linear deblocking technique, which is based on local image filters. We construct a linear filter for each relevant pixel independently, and apply these filters as post-processing. This method is limited, but nevertheless it improves the PSNR of the reconstructed images and gives visually appealing results.

关键词： Image coding Dictionaries Image reconstruction Signal processing algorithms compression algorithms Nonlinear filters Redundancy Signal representations PSNR Image storage

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Data compression for implantable medical devices

Data compression for implantable medical devices

引用

Computers in Cardiology (CinC)

作者： L.A. Koyrakh Saint Jude Medical Saint Paul MN USA

Implantable devices have limited memory, computational and battery power resources, while collecting, processing and transmitting out information from potentially many sensors. These limitations require that information within the devices be efficiently compressed. Such data compression presents a challenging task, as it must provide high fidelity of the waveform reproduction and high compression ratios on limited size data frames. Also, it must efficiently run on ultra low power hardware, and allow flexible configuration, based on the type of data to be compressed. The new compression algorithm was implemented as a bit accurate Matlab simulation, consisting of the following major steps: 1. Integer wavelet transform. 2. Quantization coupled with filtration. Two selectable quantization schemes could be utilized based on the signal properties: linear and dead-zone. Data filtration is performed on bit boundaries, which simplifies hardware implementation. The filtration thresholds are made different in different wavelet sub-bands, controlled by a single parameter. 3. Original adaptive data encoding. Our approach only requires basic logical operations such as bit counters and shifts, and is highly optimized for implementation in implantable device hardware. For high reliability each compressed data frame contains all information needed for decompression. The algorithm was applied to data from the PhysioNet ECG compression test database. 40 ECG frames of 1024 samples from 4 patients were sampled at 250 Hz, 12 bit resolution, and compressed with distortions below 8%. compression ratios were 9.3plusmn2.5, consistently exceeding 85% of the theoretical limit based on bit entropy for each individual data frame. It is concluded The compression algorithm is efficient on data collected by implantable devices, and could be used in various applications in both microprocessor and ASIC implementations, helping to reduce memory requirements and the battery energy spent on the informat

关键词： Data compression Implantable biomedical devices Hardware Filtration Batteries compression algorithms Quantization Electrocardiography Wavelet transforms Encoding

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ECG signal compression based on MSPIHT algorithm

ECG signal compression based on MSPIHT algorithm

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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Zhelong Wang Ying Chen School of Electronic and Information Engineering Dalian University of Technology Dalian Liaoning China

A new electrocardiogram (ECG) signal compression algorithm named modified set partitioning in hierarchical trees (MSPIHT), which is based on the SPIHT algorithm, has been proposed in this paper. Several measures have been taken to improve the SPIHT algorithm and these measures includes that the lifting wavelet transform is adopted, the extended zerotree structure is redefined, and the threshold optimization. Simulation experiments by using the MSPIHT algorithm and several other compression algorithms have been conducted to verify the validity of the MSPIHT algorithm and test its performance. The experimental results show that the proposed MSPIHT algorithm is valid and can achieve the better compression performance than other compression algorithms based on the wavelet transform.

关键词： Electrocardiography Wavelet transforms compression algorithms Partitioning algorithms Parameter extraction Biomedical measurements Testing Frequency Data compression Neural networks

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