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Lossless audio codec based on CNN, weighted tree and arithmetic encoding (LACCWA)

MULTIMEDIA TOOLS AND APPLICATIONS 2023年第16期83卷 48737-48759页

作者： Debnath, Asish Mondal, Uttam Kr. Tata Consultancy Serv Ltd Kolkata 700156 W Bengal India Vidyasagar Univ Dept Comp Sci Midnapore 721102 W Bengal India

In this paper, an integrated lossless audio codec with improved compression ratio has been proposed using traditional methods as well as convolutional neural network (CNN) architecture without losing any audio information. The method applies adaptive arithmetic encoding followed by binary weighted tree based transform and convolutional neural network (CNN) respectively. The first level of compression uses adaptive arithmetic encoding to process audio samples block by block, reducing the size of the data to the number of blocks. Subsequently, each of the arithmetic encoded values for every block is encoded by the binary weighted tree based encoding. Estimating a dynamic weighted path, it transforms the arithmetic-encoded data into an equivalent binary pattern. The binary stream is further compressed with latent space representations using a proposed CNN architecture. The analysis of the simulation results are performed using various statistical and robustness characteristics and comparison with other existing methods.

关键词： Lossless compression Convolutional Neural Network (CNN) Latent space arithmetic encoding Weighted tree CNNED Deep neural networks(DNN)

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Shape compression of moving objects using context-based arithmetic encoding

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2000年第7-8期15卷 601-617页

作者： Brady, N Bossen, F Dublin City Univ Teltec Ireland Dublin 9 Ireland EPFL Signal Proc Lab CH-1015 Lausanne Switzerland

This paper deals with an approach to the compression of 2-D shape information. Specifically, the approach utilises a block-based context-based arithmetic encoding method to exploit both spatial and temporal redundancy in sequences of shapes. The method is shown to be highly efficient in comparative tests. In addition, it is demonstrated that context-based arithmetic encoding is easily extended for the coding of interlaced shape sources and for encoding any source in a scalable and/or error resilient manner. The application of the technique is in the compression of video object shapes within the framework of object-based video coding. The proposed algorithm is part of the MPEG-4 video specification. (C) 2000 Elsevier Science B.V. All rights reserved.

关键词： shape coding arithmetic encoding JBIG MPEG-4

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A Block Adaptive Near-Lossless Compression Algorithm for Medical Image Sequences and Diagnostic Quality Assessment

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JOURNAL OF DIGITAL IMAGING 2020年第2期33卷 516-530页

作者： Sharma, Urvashi Sood, Meenakshi Puthooran, Emjee Jaypee Univ Informat Technol Dept Elect & Commun Waknaghat HP India

The near-lossless compression technique has better compression ratio than lossless compression technique while maintaining a maximum error limit for each pixel. It takes the advantage of both the lossy and lossless compression methods providing high compression ratio, which can be used for medical images while preserving diagnostic information. The proposed algorithm uses a resolution and modality independent threshold-based predictor, optimal quantization (q) level, and adaptive block size encoding. The proposed method employs resolution independent gradient edge detector (RIGED) for removing inter-pixel redundancy and block adaptive arithmetic encoding (BAAE) is used after quantization to remove coding redundancy. Quantizer with an optimum q level is used to implement the proposed method for high compression efficiency and for the better quality of the recovered images. The proposed method is implemented on volumetric 8-bit and 16-bit standard medical images and also validated on real time 16-bit-depth images collected from government hospitals. The results show the proposed algorithm yields a high coding performance with BPP of 1.37 and produces high peak signal-to-noise ratio (PSNR) of 51.35 dB for 8-bit-depth image dataset as compared with other near-lossless compression. The average BPP values of 3.411 and 2.609 are obtained by the proposed technique for 16-bit standard medical image dataset and real-time medical dataset respectively with maintained image quality. The improved near-lossless predictive coding technique achieves high compression ratio without losing diagnostic information from the image.

关键词： Near-lossless compression Quantizer Gradient edge detector arithmetic encoding Entropy coding

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S³DES - Scalable Software Support for Dependable Embedded Systems 32nd

S<SUP>3</SUP>DES - Scalable Software Support for Dependable ...

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32nd International Conference on Computer Architecture (ARCS)

作者： Osinski, Lukas Mottok, Juergen Tech Univ Appl Sci Regensburg Lab Safe & Secure Syst LaS3 Regensburg Germany

ISBN: (纸本)9783030186562;9783030186555

Scalable Software Support for Dependable Embedded Systems ((SDES)-D-3) achieves fault tolerance by utilizing spatial software-based triple modular redundancy for computational and voter processes on application level. Due to the parallel execution of the replicas on distinct CPU cores it makes a step towards software-based fault tolerance against transient and permanent random hardware errors. Additionally, the compliance with real-time requirements in terms of response time is enhanced compared to similar approaches. The replicated voters, the introduced mutual voter monitoring and the optimized arithmetic encoding allow the detection and compensation of voter failures without the utilization of backward recovery. Fault injection experiments on real hardware reveal that S-3 DES can detect and mask all injected data and program flow errors under a single fault assumption, whereas an uncoded voting scheme yields approx. 12% silent data corruptions in a similar experiment.

关键词： Fault tolerance Multi-core arithmetic encoding Triple modular redundancy Replicated voting

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Analyzing Echo-state Networks Using Fractal Dimension

Analyzing Echo-state Networks Using Fractal Dimension

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) / IEEE World Congress on Computational Intelligence (IEEE WCCI) / International Joint Conference on Neural Networks (IJCNN) / IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Mayer, Norbert Michael Obst, Oliver Natl Chung Cheng Univ Dept Elect Engn Chiayi Taiwan Natl Chung Cheng Univ Adv Inst Mfg High Tech Innovat Chiayi Taiwan Western Sydney Univ Ctr Res Math & Data Sci Sydney NSW Australia

ISBN: (数字)9781728186719

ISBN: (纸本)9781728186719

This work joins aspects of reservoir optimization, information-theoretic optimal encoding, and at its center fractal analysis. We build on the observation that, due to the recursive nature of recurrent neural networks, input sequences appear as fractal patterns in their hidden state representation. These patterns have a fractal dimension that is lower than the number of units in the reservoir. We show potential usage of this fractal dimension with regard to optimization of recurrent neural network initialization. We connect the idea of "ideal" reservoirs to lossless optimal encoding using arithmetic encoders. Our investigation suggests that the fractal dimension of the mapping from input to hidden state shall be close to the number of units in the network. This connection between fractal dimension and network connectivity is an interesting new direction for recurrent neural network initialization and reservoir computing.

关键词： Reservoir Computing Echo-state Networks Recurrent Neural Networks Fractals arithmetic encoding

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Word-Based Forward Coding

Word-Based Forward Coding

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Data Compression Conference (DCC)

作者： Zavadskyi, Igor Klein, Shmuel T. Shapira, Dana Natl Univ Kyiv Cybernet Dept UA-03022 Kiev Ukraine Bar Ilan Univ Dept Comp Sci IL-52900 Ramat Gan Israel Ariel Univ Dept Comp Sci IL-40700 Ariel Israel

ISBN: (纸本)9798350385885;9798350385878

This paper extends the forward-looking approach to handle alphabets of words, which leads to further compression savings. It introduces an efficient encoding for the header information, specifically the exact frequencies of the alphabet elements. Moreover, an alternative ordering method for compressing word-based dictionaries is proposed, emphasizing the benefits of forward-looking adaptive compression. Experimental results demonstrate the effectiveness of the proposed approach.

关键词： adaptive compression arithmetic encoding Huffman coding

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Parity-preserving transformations in computer arithmetic

Parity-preserving transformations in computer arithmetic

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Conference on Advanced Signal Processing Algorithms, Architectures and Implementations XII

作者： Parhami, B Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

ISBN: (纸本)0819445584

Parity checking comprises a low-redundancy method for the design of reliable digital systems. While quite effective for detecting single-bit transmission or storage errors, parity encoding has not been widely used for checking the correctness of arithmetic results because parity is not preserved during arithmetic operations and parity prediction requires fairly complex circuits in most cases. We propose a general strategy for designing parity-checked arithmetic circuits that takes advantage of redundant intermediate representations. Because redundancy is often used for high performance anyway, the incremental cost of our proposed method is quite small. Unlike conventional binary numbers, redundant representations can be encoded and manipulated in such a way that parity is preserved in each step. Additionally, lack of carry propagation ensures that the effect of a fault is localized rather than catastrophic. After establishing the framework for our parity-preserving transformations in computer arithmetic, we illustrate some applications of the proposed strategy to the design of parity-checked adder/subtractors, multipliers, and other arithmetic structures used in signal processing.

关键词： arithmetic encoding error code fault tolerance parity checking redundant format reliable computation

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File System Shield (FSS): A Pass-Through Strategy Against Unwanted Encryption in Network File Systems 1

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19th International Workshop on Security on Advances in Information and Computer Security (IWSEC)

作者： Mahboubi, Arash Camtepe, Seyit Ansari, Keyvan Pawlowski, Marcin Morawiecki, Pawel Duda, Jarek Pieprzyk, Josef Charles Sturt Univ Port Macquarie Australia Artificial Intelligence & Cyber Futures Inst Port Macquarie Australia CSIRO Canberra ACT Australia Murdoch Univ Murdoch WA Australia Jagiellonian Univ Krakow Poland Polish Acad Sci Warsaw Poland

ISBN: (数字)9789819777372

ISBN: (纸本)9789819777365;9789819777372

This study introduces the Digital Immunity Module (DIM), a novel pass-through file system gateway, positioned strategically between storage and endpoints to enhance the security of files accessed via network protocols such as NFS and SMB on SharePoint. DIM serves as a protective layer against ransomware, designed with dual objectives: (1) detecting statistical anomalies that may indicate potential encryption within the network file system, and (2) proactively expanding under-attack files using a reverse source-coding algorithm to deprive ransomware of the resources it needs to operate. For practical deployment, we have developed a proxy gateway that connects endpoints to Azure storage using the SMB protocol. This setup effectively differentiates between benign and malicious activities without needing to identify specific processes at the endpoints, i.e., a critical advantage in combating fileless ransomware, which often eludes conventional security mechanisms such as behavioral analysis. Upon detecting malicious encryption, DIM reacts by expanding the size of buffer blocks, preventing ransomware from accessing subsequent files and frequently causing the ransomware to self-terminate. Our comprehensive evaluation, involving a benign dataset of 11,928 files against 75 ransomware families, including fileless types, demonstrates that DIM significantly impedes and often terminates ransomware operations early in the attack life cycle. This confirms the practicality and effectiveness of this pass-through defence strategy.

关键词： Ransomware Information Theory Filesystem in Userspace arithmetic encoding Fileless

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Fast Monotonicity Preserving Text Sorting On GPU

Fast Monotonicity Preserving Text Sorting On GPU

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40th IEEE International Performance, Computing, and Communications Conference (IPCCC)

作者： Xu, Haoke Li, Xiaoming Univ Delaware Dept Elect & Comp Eng Newark DE 19716 USA

ISBN: (纸本)9781665443319

Sorting text is a commonly encountered computing problem in science and consumer applications. In particular, many of those applications, such as social media or data intelligence types, need to sort huge amount of text data. This motivate the development of parallel text sorting algorithms on modern computer platforms such as GPU. Text sorting and the commonly tackled sorting problems are very different, in that text sorting need to deal with variable key length and highly skewed data distribution, both of which introduce significant challenges to the parallelization of text sorting. Furthermore, GPU's architecture characteristics is not a native good match of text sorting's computation pattern. Existing text sorting algorithms are mostly comparison-based, which will lead to thread divergence on GPU, a performance. There are a small number of "radix" sorting algorithms for text. However, they all treat text as character based data, and lead to significant waste on memory space. In this paper, we propose a monotonicity preserving text transformation technique that can map text strings into fixed-length keys. The main innovation is that we carefully keep the original order of the strings during the transformation, i.e., monotonicity preserving, so that transformed keys can be safely radix sorted, in lieu of sorting the original much longer text strings. Our technical can efficiently parallelize the transformed sorting on GPU, and deal with the typical skewed text data distribution in real world applications. Compared with Thrust, a widely used library on GPU, our algorithm outperforms Thrust's string sorting method with substantial margins. We achieve the average speed up of 2.68 and the max speedup 8.5.

关键词： text sorting monotonicity arithmetic encoding

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A video coder for low bitrate mobile video streaming

A video coder for low bitrate mobile video streaming

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Conference on Visual Communications and Image Processing 2003

作者： Moschetti, F Sugimoto, K NTT DoCoMo Multimedia Labs Yokosuka Kanagawa Japan

ISBN: (纸本)0819450235

Achieving very low bitrates for video applications in a mobile environment is essential. Video codecs standards evolution had a tremendous impact in the development of digital video, making possible today widespread usage of video data. At the same time it had an impact on the direction of research, biasing most of the efforts towards block based video. Alternative approaches may though lead towards different architectures able to provide higher compression efficiency. In this paper we propose a Matching Pursuit (MP) based video coder that adopts a generalized sub-pixel motion compensation and arithmetic coding. We introduce a new dictionary, and an adaptive grid for atom coding combined with an arithmetic coder. Comparison with H.264 show an improvement of up to 20% in compression efficiency for the same PSNR.

关键词： matching pursuit arithmetic encoding overlapped motion estimation video coding

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