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Algorithmic complexity of financial motions

RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE 2014年 30卷 336-347页

作者： Brandouy, Olivier Delahaye, Jean-Paul Ma, Lin Zenil, Hector Univ Paris 01 Sorbonne Grad Business Sch IAE Paris France Univ Lille 1 Lab Informat Fondamentale Lille Villeneuve Dascq France Univ Lille 1 Ecol Univ Management Villeneuve Dascq France Univ Paris 1 Pantheon Sorbonne IHPST Paris France Univ Sheffield Dept Comp Sci Sheffield S Yorkshire England

We survey the main applications of algorithmic (Kolmogorov) complexity to the problem of price dynamics in financial markets. Westress the differences between these works and put forward a general algorithmic framework in order to highlight its potential forfinancial data analysis. This framework is "general" in the sensethat it is not constructed on the common assumption that pricevariations are predominantly stochastic in nature. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Algorithmic information theory Kolmogorov complexity Financial returns Market efficiency compression algorithms Informationtheory randomness Price movements Algorithmic probability

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Adapting Boyer-Moore-Like algorithms for Searching Huffman Encoded Texts

Adapting Boyer-Moore-Like Algorithms for Searching Huffman E...

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14th Prague Stringology Conference (PSC)

作者： Cantone, Domenico Faro, Simone Giaquinta, Emanuele Univ Catania Dipartimento Matemat & Informat I-95125 Catania Italy

ISBN: (纸本)9788001044032

In this paper we propose an efficient approach to the compressed string matching problem on Huffman encoded texts, based on the BOYER-MOORE strategy. Once a candidate valid shift has been located, a subsequent verification phase checks whether the shift is codeword aligned by taking advantage of the skeleton tree data structure. Our approach leads to algorithms with a suhlinear behavior on the average, as shown by extensive experimentation.

关键词： string matching compression algorithms Huffman codling Bayer-Moore algorithm text processing information retrieval

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Using Finite Moment Rate of Innovation for LIDAR Waveform Complexity Estimation

Using Finite Moment Rate of Innovation for LIDAR Waveform Co...

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44th Asilomar Conference on Signals, Systems and Computers

作者： Castorena, J. Creusere, C. D. Voelz, D. Klipsch Sch Elect & Comp Engn Las Cruces NM 88003 USA

ISBN: (纸本)9781424497218

LIDAR sensing collects data to obtain detailed topographical information about a region. A major challenge here is the large amount of data that needs to be collected for accurate surface reconstruction which in turn imposes significant storage, processing and transmission requirements. Current efforts to solve this problem have been focusing on applying compression algorithms to the range measurements. This process, however, requires the collection of large amounts of data, most of which is ultimately discarded. Instead, our approach is to apply a compressive sensing paradigm to sparsely sample the scene using the estimated pulse complexity to characterize the scene complexity, thus determining the number of samples needed for accurate reconstruction. As a first step towards this goal, we characterize here the individual laser return pulses for scenes of varying complexity, assuming that the pulses are composed by a finite number of innovations. Each scene is thus sampled at a rate that is much lower than the traditional Nyquist/Shannon limit. Our results show that accurate classifications of waveform and scene complexity with the simple nearest neighbor classifier are obtained using the proposed algorithm.

关键词： Technological Innovations waveforms Surface reconstruction Lidar Pulses compression algorithms Ranging measurements Legumes Complexity ON-SCENE large volume data Nearest neighbor Finite Data Collection Methods

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Identifying Hierarchical Structures in Sequences on GPU 14

Identifying Hierarchical Structures in Sequences on GPU

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13th IEEE International Symposium on Parallel and Distributed Processing with Applications

作者： Jalan, Prashant Jain, Arihant Kumar Roy, Subhajit Indian Inst Technol Dept Comp Sci & Engn Kanpur Uttar Pradesh India

ISBN: (纸本)9781467379526

Identifying hierarchical structures in sequences is an important problem with applications in lossless data-compression to program profiling. A popular algorithm for identifying hierarchical structures in sequences is the Sequitur algorithm developed by Nevill-Manning and Witten. Sequitur is not just a compression algorithm;it attempts to learn the hierarchical structure of the input sequence as a context-free grammar. However, Sequitur is difficult to parallelize. Inspired by Sequitur, we have developed a new GPU algorithm, that reveals the hierarchical structure in sequences and is also concurrency-friendly. Our algorithm, Pequitur, is built as a series of fast kernels (for intermittent synchronization), where each kernel attempts to minimize inter-thread communication and achieve a good load balance among the GPU threads. As opposed to Sequitur, Pequitur follows a greedy strategy to find good productions, that are productions formed by long and frequent substrings. We have implemented and evaluated our algorithm on the NVIDIA K20c card on random strings drawn from multiple distributions. On our benchmarks, Pequitur achieves an average speedup of more than 3X over an optimized Sequitur implementation with similar compression ratios.

关键词： hierarchical structure Input sequence GRAPPER PICK UP Graphics Processing Unit Sequences algorithms compression algorithms Load balancing Hierarchical compression ratio Seeds

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FaceCerts

FaceCerts

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Data compression Conference 2003 (DCC2003)

作者： Kirovski, D Jojic, N Microsoft Res Redmond WA 98052 USA

ISBN: (纸本)0769518966

Summary form only given. The proposed electronic systems for personal ID verification need to connect to a remote database and retrieve a stored photo for the comparison with the image on the ID. Unlike these systems, FaceCerts is an off-line person identification system that relies on public-key cryptography for provable security, while deploying a standard-quality low-cost color printing process. The basic requirement for the face compression algorithm in this system is discussed. A simple printing and scanning process combined with the face compression and matching software provides strong reliability of the FaceCerts system, resulting in relatively low likelihood of false negatives and cryptographically strong likelihood of a false positive. © 2003 IEEE.

关键词： Character recognition compression algorithms Cryptography Face detection Image coding Intrusion detection Principal component analysis Printers Printing Public key

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Adaptive Decomposition OF TV Images 2

Adaptive Decomposition OF TV Images

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2nd International Conference on Information and Telecommunication Technologies and Radio Electronics (UkrMiCo)

作者： Gofaizen, Oleg Osharovska, Olena Patlayenko, Mikola Pyliavskyi, Volodymyr OS Popov Odessa Natl Acad Telecommun Dept Radio & Televis Broadcasting Odessa Ukraine

ISBN: (纸本)9781538610565

The paper presents the results of modeling adaptive decomposition for ultra-high definition television, which provides image compression without subjective deterioration of quality. The decomposition of the images was carried out in the spectral region for the cases of wavelet analysis and Fourier transformation, depending on the signal-to-noise ratio at the image edges. Quantitative estimates of the root-mean-square error in the reconstruction of the image and the dependence of the signal-to-noise ratio on the edges on the compression coefficient are given. The number of non-zero components to be transmitted for the luminance and color difference components at two and three decomposition levels is calculated.

关键词： Wavelet transform image compression compression algorithms decomposition signal/noise ratio

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Mask Motion Adaptive medical image coding

Mask Motion Adaptive medical image coding

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IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)

作者： Mhedhbi, Imen Kaddouh, Fayez Hachicha, Khalil Heudes, Didier Hochberg, Sylvain Garda, Patrick Univ Paris 06 Sorbonne Univ UMR 7606 LIP6 F-75005 Paris France CNRS UMR 7606 LIP6 F-75005 Paris France APHP EGP Paris France CIRA Paris France

ISBN: (纸本)9781479921317

We combine a mask motion detection algorithm with both the WAAVES adaptive compression algorithm resulting into MMWaaves) and a JPEG2000 coder resulting into MMJPEG2000) for the compression of medical images sequences. Several images were compressed using Waaves, MMWaaves, and MMJPEG2000 to observe which tool provided the best visual quality while maintaining a high compression ratio. Compared to Waaves, the MMWaaves achieved compression gains up to 40% for CT scans and 50 % for MRI. In addition, the SSIM values attributed to the compressed images were between 0.96 and 0.988 while the PSNR values were higher than 42. In addition MMWaaves attained a superior performance than MMJPEG2000.

关键词： Computed tomography Image coding Magnetic resonance imaging Medical diagnostic imaging Motion detection Transform coding image coding Motion detection transform coding X-Ray Computed Tomography Magnetic Resonance Imaging diagnostic imaging compression ratio compression algorithms Masks

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Assessing File Formats for Static Image Transmission

Assessing File Formats for Static Image Transmission

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2006 International Telecommunications Symposium (ITS)

作者： Lins, R. D. de Sa Rodrigues, C. M. Univ Fed Pernambuco Ctr Technol & Geosci Dept Elect & Syst Telecommun Grp Recife PE Brazil

This paper presents a comparative analysis between the three most important progressive file formats: PING, JPEG and JPEG2000. Several types of images and features have been analyzed. This analysis provides elements f... 详细信息

ISBN: (纸本)9781424436446

关键词： compression algorithms image storage image transmission JPEG PNG JPEG2000 Computer Networks

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A novel data compression algorithm for dynamic data

A novel data compression algorithm for dynamic data

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IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering, SIBIRCON

作者： Rahul Gupta Ashutosh Gupa Suneeta Agarwal MNNIT Allahabad India IART Allahabad India

ISBN: (纸本)9781424421336

This paper presents a compression algorithm for dynamic data, the size of which keeps on increasing rapidly. It is a memory efficient data compression technique comprising of a block approach that keeps the data in compressed form as long as possible and enables the data to be appended to the already compressed text. The algorithm requires only a minimal decompression for supporting update of data using a little preprocessing which reduces the unnecessary time spent in compression-decompression to support update by the algorithms deigned till now to a minimum. Further, the text document can be modified as required without decompressing and again compressing the whole document. The paper also presents the design of the required data structures for our algorithm with performance results.

关键词： Indexes Heuristic algorithms Algorithm design and analysis compression algorithms Data structures Data compression Region 8

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Training Swinging Door Trending compression Algorithm for IoT devices

Training Swinging Door Trending Compression Algorithm for Io...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Juan David Arias Correa Alex Sandro Roschildt Pinto Carlos Montez Post-graduate Program of Automation Systems Engineering Federal University of Santa Catarina (UFSC) Florianópolis Brazil Dept. of Informatics and Statistic Dept. of Automation and Systems Engineering Federal University of Santa Catarina (UFSC) Florianópolis Brazil

ISBN: (数字)9798350373011

ISBN: (纸本)9798350373028

The communication system is essential for the devices used in IoT. Nevertheless, the consumption caused by transmitting and receiving data is a concern in many scenarios. That is due to these devices commonly having limited energy and computational capacities. Transmission of redundant or irrelevant samples frequently wastes the device’s resources. Furthermore, Storing a large amount of redundant data could consume storage space and not offer any benefit. Data compression (DC) methods are a potential solution. DC could reduce communication usage and storage demand. This research proposes the Training Swing Door Trending (TSDT) for being implemented in IoT Devices. TSDT is a new algorithm that improves the classic Swing Door Trending (STD). They represent the data by trend lines and have a constant computational complexity. TSDT has a training step for the automatic configuration of its parameters. This article additionally presents the compression Factor (C-Score), a new quality metric to analyze the compression results in lossy DC methods. C-Score takes as a basis the F-Score, a measure of predictive performance. The C-Score uses the compression and Error metrics to evaluate the compression performance in Lossy algorithms.

关键词： Training Performance evaluation Communication systems Data compression Prediction algorithms Market research Internet of Things Computational complexity compression algorithms

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