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Molecular arithmetic coding (MoAC) and Optimized Molecular Prefix coding (MoPC) for Diffusion-Based Molecular Communication

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IEEE TRANSACTIONS ON MOLECULAR BIOLOGICAL AND MULTI-SCALE COMMUNICATIONS 2025年第1期11卷 66-77页

作者： Sahin, Melih Ortlek, Beyza Ezgi Akan, Ozgur B. Koc Univ Ctr Next Generat Commun Dept Elect & Elect Engn TR-34450 Istanbul Turkiye Univ Cambridge Dept Engn Internet Everything Grp Cambridge CB3 0FA England

Molecular communication (MC) enables information transfer through molecules at the nano-scale. This paper presents new and optimized source coding (data compression) methods for MC. In a recent paper, prefix source coding was introduced into the field, through an MC-adapted version of the Huffman coding. We first show that while MC-adapted Huffman coding improves symbol error rate (SER), it does not always produce an optimal prefix codebook in terms of coding length and power. To address this, we propose optimal molecular prefix coding (MoPC). The major result of this paper is the Molecular arithmetic coding (MoAC), which we derive based on an existing general construction principle for constrained arithmetic channel coding, equipping it with error correction and data compression capabilities for any finite source alphabet. We theoretically and practically show the superiority of MoAC to SAC, our another adaptation of arithmetic source coding to MC. However, MoAC's unique decodability is limited by bit precision. Accordingly, a uniquely-decodable new coding scheme named Molecular arithmetic with Prefix coding (MoAPC) is introduced. On two nucleotide alphabets, we show that MoAPC has a better compression performance than optimized MoPC. MC simulation results demonstrate the effectiveness of the proposed methods.

关键词： Encoding Codes arithmetic Symbols Molecular communication Source coding Huffman coding Decoding Transmitters Receivers Molecular communication (MC) data compression arithmetic coding prefix coding run-length-limited coding

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arithmetic coding as a non-linear dynamical system

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2009年第4期14卷 1013-1020页

作者： Nagaraj, Nithin Vaidya, Prabhakar G. Bhat, Kishor G. Natl Inst Adv Studies Sch Nat Sci & Engn Bangalore 560012 Karnataka India

In order to perform source coding (data compression), we treat messages emitted by independent and identically distributed sources as imprecise measurements (symbolic sequence) of a chaotic, ergodic, Lebesgue measure preserving, non-linear dynamical system known as Generalized Luroth Series (GLS). GLS achieves Shannon's entropy bound and turns out to be a generalization of arithmetic coding, a popular source coding algorithm, used in international compression standards such as JPEG2000 and H.264. We further generalize GLS to piecewise non-linear maps (Skewed-nGLS). We motivate the use of Skewed-nGLS as a framework for joint source coding and encryption. (c) 2007 Elsevier B.V. All rights reserved.

关键词： Data compression Encryption Chaotic map arithmetic coding Source coding

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arithmetic coding using hierarchical dependency context model for H.264/AVC video coding

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MULTIMEDIA TOOLS AND APPLICATIONS 2016年第12期75卷 7351-7370页

作者： Gao, Min Wang, Qiang Zhao, Debin Gao, Wen Harbin Inst Technol Dept Comp Sci & Technol Harbin 150006 Peoples R China

In this paper, a hierarchical dependency context model (HDCM) is firstly proposed to exploit the statistical correlations of DCT (Discrete Cosine Transform) coefficients in H.264/AVC video coding standard, in which the number of non-zero coefficients in a DCT block and the scanned position are used to capture the magnitude varying tendency of DCT coefficients. Then a new binary arithmetic coding using hierarchical dependency context model (HDCMBAC) is proposed. HDCMBAC associates HDCM with binary arithmetic coding to code the syntax elements for a DCT block, which consist of the number of non-zero coefficients, significant flag and level information. Experimental results demonstrate that HDCMBAC can achieve similar coding performance as CABAC at low and high QPs (quantization parameter). Meanwhile the context modeling and the arithmetic decoding in HDCMBAC can be carried out in parallel, since the context dependency only exists among different parts of basic syntax elements in HDCM.

关键词： arithmetic coding Context modeling DCT coefficient coding H.264/AVC

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arithmetic coding and blinding countermeasures for lattice signatures Engineering a side-channel resistant post-quantum signature scheme with compact signatures

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JOURNAL OF CRYPTOGRAPHIC ENGINEERING 2018年第1期8卷 71-84页

作者： Saarinen, Markku-Juhani O. Dark Matter LLC Abu Dhabi U Arab Emirates

We describe new arithmetic coding techniques and side-channel blinding countermeasures for lattice-based cryptography. Using these techniques, we develop a practical, compact, and more quantum-resistant variant of the BLISS Ideal Lattice Signature Scheme. We first show how the BLISS parameters and hash-based random oracle can be modified to be more secure against quantum pre-image attacks while optimizing signature size. arithmetic coding offers an information theoretically optimal compression for stationary and memoryless sources, such as the discrete Gaussian distributions often present in lattice-based cryptography. We show that this technique gives better signature sizes than the previously proposed advanced Huffman-based signature compressors. We further demonstrate that arithmetic decoding from an uniform source to target distribution is also an optimal non-uniform sampling method in the sense that a minimal amount of true random bits is required. Performance of this new Binary arithmetic coding sampler is comparable to other practical samplers. The same code, tables, or circuitry can be utilized for both tasks, eliminating the need for separate sampling and compression components. We then describe simple randomized blinding techniques that can be applied to anti-cyclic polynomial multiplication to mask timing-and power consumption side-channels in ring arithmetic. We further show that the Gaussian sampling process can also be blinded by a split-and-permute techniques as an effective countermeasure against side-channel attacks.

关键词： Lattice signatures arithmetic coding Side-channel countermeasures Quantum-resistant cryptography BLISS

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arithmetic coding-Based 5-Bit Weight Encoding and Hardware Decoder for CNN Inference in Edge Devices

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IEEE ACCESS 2021年 9卷 166736-166749页

作者： Lee, Jong Hun Kong, Joonho Munir, Arslan Kyungpook Natl Univ Sch Elect & Elect Engn Daegu 41566 South Korea Kyungpook Natl Univ Sch Elect Engn Daegu 41566 South Korea Kansas State Univ Dept Comp Sci Manhattan KS 66506 USA

Convolutional neural networks (CNNs) have gained a huge attention for real-world artificial intelligence (AI) applications such as image classification and object detection. On the other hand, for better accuracy, the size of the CNNs' parameters (weights) has been increasing, which in turn makes it difficult to enable on-device CNN inferences in resource-constrained edge devices. Though weight pruning and 5-bit quantization methods have shown promising results, it is still challenging to deploy large CNN models in edge devices. In this paper, we propose an encoding and hardware-based decoding technique which can be applied to 5-bit quantized weight data for on-device CNN inferences in resource-constrained edge devices. Given 5-bit quantized weight data, we employ arithmetic coding with range scaling for loss-less weight compression, which is performed offline. When executing on-device inferences with underlying CNN accelerators, our hardware decoder enables a fast in-situ weight decompression with small latency overhead. According to our evaluation results with five widely used CNN models, our arithmetic coding-based encoding method applied to 5-bit quantized weights shows a better compression ratio by 9.6x while also reducing the memory data transfer energy consumption by 89.2%, on average, as compared to the case of uncompressed 32-bit floating-point weights. When applying our technique to pruned weights, we obtain better compression ratios by 57.5x-112.2x while reducing energy consumption by 98.3%-99.1% as compared to the case of 32-bit floating-point weights. In addition, by pipelining the weight decoding and transfer with the CNN execution, the latency overhead of our weight decoding with 16 decoding unit (DU) hardware is only 0.16%-5.48% and 0.16%-0.91% for non-pruned and pruned weights, respectively. Moreover, our proposed technique with 4-DU decoder hardware reduces system-level energy consumption by 1.1%-9.3%.

关键词： Convolutional neural networks arithmetic coding weight compression edge devices 5-bit quantization

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arithmetic coding-based continuous error detection for efficient ARQ-based image transmission

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2000年第6期18卷 861-867页

作者： Chou, J Ramchandran, K Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94708 USA

Block cyclic redundancy check (CRC) codes are typically used to perform error detection in Automatic Repeat Request (ARQ) protocols for data communications. Although efficient, CRC's can detect errors only after an entire block of data has been received and processed. In this paper, we propose a new "continuous" error detection scheme using arithmetic coding that provides a novel tradeoff between the amount of added redundancy and the amount of time needed to detect an error once it occurs. This method of error detection, first introduced by Bell, Witten, and Cleary, is achieved through the use of an arithmetic codec, and has the attractive feature that it can be combined physically with arithmetic source coding, which is widely used in state-of-the-art image coders. We analytically optimize the tradeoff between added redundancy and error-detection time, achieving significant gains in bit rate throughput over conventional ARQ schemes for Binary Symmetric Channel models for all probabilities of error.

关键词： arithmetic coding ARQ error detection

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arithmetic coding FOR DATA-COMPRESSION

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PROCEEDINGS OF THE IEEE 1994年第6期82卷 857-865页

作者： HOWARD, PG VITTER, JS DUKE UNIV DEPT COMP SCIDURHAMNC 27708

arithmetic coding provides an effective mechanism for removing redundancy in the encoding of data. We show how arithmetic coding works and describe an efficient implementation that uses table lookup as a fast alternative to arithmetic operations. The reduced-precision arithmetic has a provably negligible effect on the amount of compression achieved. We can speed up the implementation further by use of parallel processing. We discuss the role of probability models and how they provide probability information to the arithmetic coder. We conclude with perspectives on the comparative advantages and disadvantages of arithmetic coding.

关键词： arithmetic coder arithmetic coding arithmetic operations data compression data compression encoding encoding negligible effect parallel processing parallel processing probability information probability models reduced-precision arithmetic redundancy table lookup table lookup

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arithmetic coding revisited

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ACM TRANSACTIONS ON INFORMATION SYSTEMS 1998年第3期16卷 256-294页

作者： Moffat, A Neal, RM Witten, IH Univ Melbourne Dept Comp Sci Parkville Vic 3052 Australia Univ Toronto Dept Comp Sci Toronto ON Canada Univ Toronto Dept Stat Toronto ON Canada Univ Waikato Dept Comp Sci Hamilton New Zealand

Over the fast decade, arithmetic coding has emerged as an important compression tool. It is now the method of choice for adaptive coding on multisymbol alphabets because of its speed, low storage requirements, and effectiveness of compression. This article describes a new implementation of arithmetic coding that incorporates several improvements over a widely used earlier version by Witten, Neal, and Cleary, which has become a de facto standard. These improvements include fewer multiplicative operations, greatly extended range of alphabet sizes and symbol probabilities, and the use of low-precision arithmetic, permitting implementation by fast shift/add operations. We also describe a modular structure that separates the coding, modeling, and probability estimation components of a compression system. To motivate the improved coder, we consider the needs of a word-based text compression program. We report a range of experimental results using this and other models. Complete source code is available.

关键词： algorithms performance approximate coding arithmetic coding text compression word-based model

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arithmetic coding based lossless compression schemes for power system steady state operational data

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2012年第1期43卷 47-53页

作者： Das, Sarasij Rao, P. S. Nagendra Indian Inst Sci Dept Elect Engn Bangalore 560012 Karnataka India

Introduction of processor based instruments in power systems is resulting in the rapid growth of the measured data volume. The present practice in most of the utilities is to store only some of the important data in a retrievable fashion for a limited period. Subsequently even this data is either deleted or stored in some back up devices. The investigations presented here explore the application of lossless data compression techniques for the purpose of archiving all the operational data - so that they can be put to more effective use. Four arithmetic coding methods suitably modified for handling power system steady state operational data are proposed here. The performance of the proposed methods are evaluated using actual data pertaining to the Southern Regional Grid of India. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Power system Steady state data arithmetic coding Golomb-Rice coding Data compression

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arithmetic coding INTO FIXED-LENGTH CODEWORDS

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IEEE TRANSACTIONS ON INFORMATION THEORY 1994年第1期40卷 219-223页

作者： TEUHOLA, J RAITA, T Department of Computer Science University of Turku Finland

arithmetic coding is known to be optimal in compressing strings of independent symbols, the probabilities of which are given. However the method has some disadvantages that the present variant tries to overcome. The idea here is to apply arithmetic coding piecewise, by cutting the process regularly. The result consists of fixed-length sequences of bits, representing variable-length substrings of the source. For implementation reasons, the bit sequences are composed of machine words, allowing us to use basic arithmetic efficiently. The compression gain approaches the optimum when the sequence size is increased.

关键词： arithmetic coding DATA COMPRESSION VARIABLE TO FIXED-LENGTH ENcoding

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