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Entropy and Optimal Compression of Some General Plane Trees

ACM TRANSACTIONS ON ALGORITHMS 2019年第1期15卷 1–23页

作者： Golebiewski, Zbigniew Magner, Abram Szpankowski, Wojciech Wroclaw Univ Sci & Technol Fac Fundamental Problems Technol Wroclaw Poland Purdue Univ Ctr Sci Informat W Lafayette IN 47907 USA Purdue Univ Comp Sci W Lafayette IN 47907 USA

We continue developing the information theory of structured data. In this article, we study models generating d-ary trees (d >= 2) and trees with unrestricted degree. We first compute the entropy which gives us the fundamental lower bound on compression of such trees. Then we present efficient compression algorithms based on arithmetic encoding that achieve the entropy within a constant number of bits. A naive implementation of these algorithms has a prohibitive time complexity of O(n(d)) elementary arithmetic operations (each corresponding to a number f (n(d)) of bit operations), but our efficient algorithms run in O(n(2)) of these operations, where n is the number of nodes. It turns out that extending source coding (i.e., compression) from sequences to advanced data structures such as degree-unconstrained trees is mathematically quite challenging and leads to recurrences that find ample applications in the information theory of general structures (e.g., to analyze the information content of degree-unconstrained non-plane trees).

关键词： arithmetic coding random trees plane recursive trees

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Context-Based Adaptive arithmetic Encoding of EAVQ Indices

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IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2012年第5期20卷 1473-1481页

作者： Lakhdhar, Khaled Lefebvre, Roch Univ Sherbrooke Dept Genie Elect & Genie Informat Sherbrooke PQ J1K 2R1 Canada

This paper presents a lossless compression algorithm for the binary indices of the embedded algebraic vector quantizer (EAVQ) used by the AMR-WB+ (Extendend Adaptive Multi-Rate Wide Band) codec. We present a statical study of the EAVQ indices for diverse audio types (speech, music, etc.) and we discuss the design of the lossless algorithm including the choice of different strategies. The proposed algorithm combines run length encoding (RLE) and context-based arithmetic encoding to reduce the bitrate of the EAVQ indices by about 10% at the expense of 1% rise in complexity of the codec. The proposed algorithm can increase the segmental signal to noise ratio of about 9% at low rates for speech signals and improve the subjective scores in noisy channels by about 0.5 on a five-point scale if combined with an additional protection layer.

关键词： arithmetic coding compression context-based compression embedded algebraic vector quantizer (EAVQ) extendend adaptive multi-rate wide band (AMR-WB plus ) run length coding

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GLOBAL STUDY ON DATA-COMPRESSION TECHNIQUES FOR DIGITAL CHINESE CHARACTER PATTERNS

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IEE PROCEEDINGS-E COMPUTERS AND DIGITAL TECHNIQUES 1992年第1期139卷 1-8页

作者： JU, RH JOU, IC TSAY, MK NATL CENT UNIV INST COMP SCI & ELECTR ENGNCHUNGLITAIWAN

Dot matrix representation of Chinese characters is the most popular method used, however, it requires a relatively large memory for storage of Chinese character patterns. For the purpose of a global study, various data compression techniques are investigated to determine the method that requires the least amount of memory for data storage. The entropy of Chinese character patterns preprocessed using the two-dimensional prediction algorithm show the best results and appear almost independent of the subblock resolutions of m ] n. Therefore, a possible bound of data compression for Chinese character patterns can be predicted. The data compression technique involving two-dimensional prediction preprocessing as well as arithmetic coding for subblock symbols is found to be capable of achieving the best compression results for the 13,051 Chinese character patterns with various fonts in different resolutions.

关键词： 2-DIMENSIONAL PREDICTION arithmetic coding CHINESE CHARACTER PATTERNS

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DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2020年第4期14卷 700-714页

作者： Wiedemann, Simon Kirchhoffer, Heiner Matlage, Stefan Haase, Paul Marban, Arturo Marinc, Talmaj Neumann, David Nguyen, Tung Schwarz, Heiko Wiegand, Thomas Marpe, Detlev Samek, Wojciech Fraunhofer Heinrich Hertz Inst Machine Learning Grp D-10587 Berlin Germany Fraunhofer Heinrich Hertz Inst D-10587 Berlin Germany Fraunhofer Heinrich Hertz Inst Video Coding Grp D-10587 Berlin Germany

In the past decade deep neural networks (DNNs) have shown state-of-the-art performance on a wide range of complex machine learning tasks. Many of these results have been achieved while growing the size of DNNs, creating a demand for efficient compression and transmission of them. In this work we present DeepCABAC, a universal compression algorithm for DNNs that is based on applying Context-based Adaptive Binary arithmetic Coder (CABAC) to the DNN parameters. CABAC was originally designed for the H.264/AVC video coding standard and became the state-of-the-art for the lossless compression part of video compression. DeepCABAC applies a novel quantization scheme that minimizes a rate-distortion function while simultaneously taking the impact of quantization to the DNN performance into account. Experimental results show that DeepCABAC consistently attains higher compression rates than previously proposed coding techniques for DNN compression. For instance, it is able to compress the VGG16 ImageNet model by x63.6 with no loss of accuracy, thus being able to represent the entire network with merely 9 MB. The source code for encoding and decoding can be found at https://***/fraunhoferhhi/DeepCABAC.

关键词： Neural networks Source coding Decoding Compression algorithms Quantization (signal) Machine learning Deep learning neural network compression efficient representation source coding rate-distortion quantization arithmetic coding

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Location-based data delivery between vehicles and infrastructure

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IET INTELLIGENT TRANSPORT SYSTEMS 2020年第5期14卷 288-296页

作者： Khan, Farhan Nguang, Sing Kiong Univ Auckland Fac Engn Dept Elect Comp & Software Engn 20 Symonds St Auckland New Zealand

Multi-hop routing in vehicular ad-hoc networks (VANETs) and wireless sensor networks has attracted significant interest of researchers in the wireless ad-hoc networks community. Most multi-hop routing protocols in VANET are based around the idea of choosing the next destination, which will provide the shortest-delay to reach a destination. To ensure better monitoring and reporting of road condition information, this study proposes location-based data forwarding through roadside sensors using k-shortest path routing combined with Q-learning. Q-learning is used for exploration of the sensing field to determine those sensors which have a higher queuing delay during peak hours as well as those which have comparatively lower delays. The use of Q-learning for exploration (sans routing) enables faster convergence for the sensors as compared to those techniques which utilise naive Q-learning for shortest path routing. Secondly, multi-hop routing is being combined with source coding (Huffman and arithmetic coding) to compress the data payload of packets. This has shown some promising results for the VANETs employing dedicated short-range communication.

关键词： routing protocols vehicular ad hoc networks learning (artificial intelligence) source coding Huffman codes arithmetic codes telecommunication computing data compression k-shortest path routing queuing delay sans routing naive Q-learning location-based data delivery wireless sensor networks multihop routing protocols VANET road condition information roadside sensors vehicular ad-hoc networks wireless ad-hoc networks community location-based data forwarding source coding Huffman coding arithmetic coding packet data payload short-range communication

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Secure FSM-based arithmetic codes

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SIGNAL IMAGE AND VIDEO PROCESSING 2014年第7期8卷 1263-1272页

作者： Ziyabar, Hashem Moradmand Sinaie, Mahnaz Payandeh, Ali Vakili, Vahid Tabataba Sazgan Ertebat Co Tehran Iran Tarbiat Modares Univ Dept Elect & Comp Engn Commun Syst Lab Tehran Iran Malekashtar Univ Technol Dept Elect Engn Tehran Iran Iran Univ Sci & Technol Dept Elect Engn Tehran Iran

Recently, arithmetic coding has attracted the attention of many scholars because of its high compression capability. Accordingly, in this paper, a method that adds secrecy to this well-known source code is proposed. Finite state arithmetic code is used as source code to add security. Its finite state machine characteristic is exploited to insert some random jumps during source coding process. In addition, a Huffman code is designed for each state to make decoding possible even in jumps. Being prefix-free, Huffman codes are useful in tracking correct states for an authorized user when he/she decodes with correct symmetric pseudo-random key. The robustness of our proposed scheme is further reinforced by adding another extra uncertainty by swapping outputs of Huffman codes in each state. Several test images are used for inspecting the validity of the proposed Huffman finite state arithmetic coding (HFSAC). The results of several experimental key space analyses, statistical analyses, key and plaintext sensitivity tests show that HFSAC with a little effect on compression efficiency provides an efficient and secure method for real-time image encryption and transmission.

关键词： arithmetic coding Image compression Finite state machine Huffman code Image encryption

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A probabilistic method for cooperative hierarchical aggregation of data in VANETs

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AD HOC NETWORKS 2010年第5期8卷 518-530页

作者： Lochert, Christian Scheuermann, Bjoern Mauve, Martin Univ Dusseldorf Dept Comp Sci D-40225 Dusseldorf Germany

We propose an algorithm for the hierarchical aggregation of observations in dissemination-based, distributed traffic information systems. Instead of transmitting observed parameters directly, we propose soft-state sketches an extension of Flajolet-Martin sketches as a probabilistic approximation. This data representation is duplicate insensitive, a trait that overcomes two central problems of existing aggregation schemes for VANET applications. First, when multiple aggregates of observations for the same area are available, it is possible to combine them into an aggregate containing all information from the original aggregates. This is fundamentally different from existing approaches where typically one of the aggregates is selected for further use while the rest is discarded. Second, any observation or aggregate can be included into higher-level aggregates, regardless if it has already been previously directly or indirectly added. Those characteristics result in a very flexible aggregate construction and a high quality of the aggregates. We demonstrate these traits of our approach by a simulation study. (c) 2010 Elsevier B.V. All rights reserved.

关键词： VANET Aggregation Sketch Information dissemination arithmetic coding Soft-state sketch

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Lossless Compression of Microarray Images Using Image-Dependent Finite-Context Models

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IEEE TRANSACTIONS ON MEDICAL IMAGING 2009年第2期28卷 194-201页

作者： Neves, Antonio J. R. Pinho, Armando J. Univ Aveiro Signal Proc Lab DETI IEETA P-3810193 Aveiro Portugal

The use of microarray expression data in state-of-the-art biology has been well established. The widespread adoption of this technology, coupled with the significant volume of data generated per experiment, in the form of images, has led to significant challenges in storage and query retrieval. In this paper, we present a lossless bitplane-based method for efficient compression of microarray images. This method is based on arithmetic coding driven by image-dependent multibitplane finite-context models. It produces an embedded bitstream that allows progressive, lossy-to-lossless decoding. We compare the compression efficiency of the proposed method with three image compression standards (JPEG2000, JPEG-LS, and JBIG) and also with the two most recent specialized methods for microarray image coding. The proposed method gives better results for all images of the test sets and confirms the effectiveness of bitplane-based methods and finite-context modeling for the lossless compression of microarray images.

关键词： arithmetic coding finite-context modeling image coding standards lossless image compression microarray images

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WORD-BASED TEXT COMPRESSION

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SOFTWARE-PRACTICE & EXPERIENCE 1989年第2期19卷 185-198页

作者： MOFFAT, A Department of Computer Science The University of Melbourne Parkville Victoria 3052 Australia

AbstractThe development of efficient algorithms to support arithmetic coding has meant that powerful models of text can now be used for data compression. Here the implementation of models based on recognizing and recording words is considered. Move‐to‐the‐front and several variable‐order Markov models have been tested with a number of different data structures, and first the decisions that went into the implementations are discussed and then experimental results are given that show English text being represented in under 2‐2 bits per character. Moreover the programs run at speeds comparable to other compression techniques, and are suited for prac

关键词： Data compression arithmetic coding Word‐based compression

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Hardware assisted rate distortion optimization with embedded CABAC accelerator for the H.264 advanced video codec

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2006年第2期52卷 590-597页

作者： Nunez-Yanez, J. L. Chouliaras, V. A. Alfonso, D. Rovati, F. S. Univ Bristol Dept Elect Engn Bristol BS8 1TH Avon England Loughborough Univ Technol Dept Elect Engn Loughborough LE11 3TU Leics England

This paper investigates the algorithmic complexity of rate distortion optimization and arithmetic coding in the new H. 264 video coding standard and proposes a hardware accelerator to reduce it by more than an order of magnitude. The accelerator incorporates arithmetic coding and decoding engines and efficiently handles all the context information required by RDO and CABAC in H.264. The bit stream generated by the hardware is equivalent to that generated by the JM 9.4 reference implementation. The ISA of a controlling scalar 32-bit RISC CPU has been extended with custom RDO/CABAC instructions and the accelerator prototyped in a state-of-the-art FPGA technology.

关键词： CABAC RDO arithmetic coding H.264 video coding

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