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检索条件"主题词=predictive coding"

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Forensic Analyses Based on predictive coding

Forensic Analyses Based on Predictive Coding

引用

IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS)

作者： Shuhi Hou Shanshan Dong Siuming Yiu Tetsutaro Uehara University of Science and Technology Beijing Beijing China Business Institute Anhui University of Finance and Economics Bengbu China The University of Hong Kong Hong Kong China Ritsumeikan University Kusatsu Japan

ISBN: (数字)9781728198743

ISBN: (纸本)9781728198750

Cybercrime is growing rampantly around the world, which has caused huge monetary damages in recent years. One of the major difficulties in cybercrime forensic analysis is to identify relevant digital evidence from a large amount of electronic documents. Traditional methods, such as manual inspection and keyword searching, are no longer effective both in terms of time and accuracy. In order to reduce the cost, save time and improve the accuracy of forensic investigation, the paper proposed a predictive coding scheme to study and identify relevant digital evidence. The experimental results show that the predictive coding based on semantic searching is feasible, and more efficient and accurate than the keyword searching.

关键词： predictive coding Training Mutual information Keyword search Manuals Semantics Electronic mail

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Experiments in adaptive predictive coding

Experiments in adaptive predictive coding

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Xiaobo Li V. Nehru Department of Computing Science University of Alberta Edmonton AB Canada

This paper reports experiments in image compression using adaptive sampling and predictive coding. A picture usually comprises of areas of varying detail. The authors first detect these areas, and then sample key points from them. An area with greater detail requires many sample points to suitably represent it, whereas regions with lesser detail can be represented with fewer points. These key sample points are then used to predict the remainder of the image. Combining the use of adaptive sampling with predictive encoding, the authors' algorithm manages to achieve compression while maintaining the desired image quality. Its performance is compared to JPEG in terms of compression ratio and image quality.

关键词： predictive coding Image coding Image segmentation Image sampling Image quality Wavelet transforms Iterative algorithms Quantization Pixel Tail

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Recursive and adaptive predictive coding of speech

Recursive and adaptive predictive coding of speech

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： K. Nakata K. Higure Department of Electronics Chiba Institute of Technology Narashino Chiba Japan

A new algorithm of speech coding "recursive and adaptive prediction" is proposed and tested. An adaptive linear prediction of the input is carried out sample by sample, and only predictive residuals are quantized and transmitted in binary codes. predictive coefficients are adaptively controlled by quantized prediction error. Segmental SNR of almost 22 dB is obtained at 16 kb/s by the cascade connection of 2 stages of prediction. The algorithm can handle mixed voices and be implemented by single DSP.

关键词： predictive coding Speech coding Digital signal processing Quantization Testing Binary codes Error correction codes Prediction algorithms Bit rate Delay effects

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M-Channel Multiple Description coding with Two-Rate predictive coding and Staggered Quantization

M-Channel Multiple Description Coding with Two-Rate Predicti...

引用

Data Compression Conference (DCC)

作者： Upul Samarawickrama Jie Liang School of Engineering Science Simon Fraser University Burnaby BC Canada

A low complexity multiple description (MD) coding method is proposed to generate M descriptions. Consider the MD coding of a stationary correlated source. We first fictitiously partition the source into sample blocks of size M, i.e., M polyphases. Each description encodes all input samples, but with a variable bit rate that depends on the indices of the sample and the description. A special DPCM encoder is used in each description, where each sample is predicted from the reconstructed samples in the same description. The prediction error is uniformly scalar-quantized and entropy coded.

关键词： predictive coding Quantization Image reconstruction Entropy Encoding Decoding Data compression Data engineering Bit rate Image coding

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Ordering predictive coding of digital image

Ordering predictive coding of digital image

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： S. Mizuno K. Iinuma C&C Systems Research Laboratories NEC Corporation Limited Kawasaki Kanagawa Japan

An efficient coding method for multi-level digital image data with up to about 16 levels is described, which can attain data compression nearly equal to the theoretical bound given by a two-dimensional Markov model entropy, without any loss of picture information. The method, ordering predictive coding, is composed of an ordering prediction followed by a run-length coding of a serial prediction error bit stream. It is proved that the ordering prediction is the optimized prediction scheme and has a lower prediction error entropy than that of DPCM and bit plane, and also proved that the run-length coding reduces the entropy almost near to that of the two-dimensional Markov model entropy.

关键词： predictive coding Digital images Entropy Image coding Facsimile National electric code Laboratories Data compression predictive models Propagation losses

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Rate distortion theory and predictive coding

Rate distortion theory and predictive coding

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： M. Schroeder B. Atal Drittes Physicalisches Institute Universitàť Göttingen Germany Bell Laboratories Murray Hill NJ USA

In previous papers on digital coding we have stressed the importance of taking proper account of the masking properties of the human ear in order to minimize the subjective loudness of the quantizing noise. The resulting optimal quantizing noise spectrum is in general not flat and requires the use of noise-shaping filters. This masking of the quantizing noise by the speech signal itself has allowed us to use very low bit rates (less than 1 bit/sample for the prediction residual in aa adaptive predictive coder) while maintaining high speech quality. However, if the low bit rates are realized by a (coarse) instantaneous qnantizer, the quantizing error is not white and the noise-shaping filter (in the feedback loop around the quantizer) does not produce the intended noise spectrum. In this paper, we therefore describe non-instantaneous, tree-coding methods that allow the attainment of even lower bit rates (near the theoretical rate-distortion limit) with the precise optimum noise spectrum.

关键词： Rate distortion theory predictive coding Bit rate Noise shaping Filters Speech enhancement Speech coding Humans Ear predictive maintenance

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High quality adaptive predictive coding of speech

High quality adaptive predictive coding of speech

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： M. Berouti J. Makhoul Bolt Beranek and Newman 슠Inc. Cambridge MA USA

We report on the results of research to code speech at 16 kbps under the condition that the quality of the transmitted speech be equal to that of the original. Some of the original speech had been corrupted by noise and distortions typical of long distance telephone lines. The rigorous requirements of this work led to a new outlook on adaptive predictive coding. We have found that the pitch predictor is not useful on balance and should be eliminated, and that the residual should be quantized with no clipping and encoded using a variable-length code. A single coding scheme seems to be adequate for all speech and all conditions. In addition, the adaptive predictive coding system has been modified to include a noise spectral shaping filter that effectively eliminates the perception of background granular noise.

关键词： predictive coding Speech coding Speech enhancement Background noise Quantization Degradation Roundoff errors Telephony Noise shaping Filters

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On GMM Kalman predictive coding of LSFS for packet loss

On GMM Kalman predictive coding of LSFS for packet loss

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shaminda Subasingha Manohar N. Murthi Soren Vang Andersen Department of Electrical and Computer Engineering University of Miami USA Department of Electronic Systems University of Aalborg Denmark

Gaussian mixture model (GMM)-based Kalman predictive coders have been shown to perform better than baseline GMM recursive coders in predictive coding of line spectral frequencies (LSFs) for both clean and packet loss conditions However, these stationary GMM Kalman predictive coders were not specifically designed for operation in packet loss conditions. In this paper, we demonstrate an approach to the the design of GMM-based predictive coding for packet loss channels. In particular, we show how a stationary GMM Kalman predictive coder can be modified to obtain a set of encoding and decoding modes, each with different Kalman gains. This approach leads to more robust performance of predictive coding of LSFs in packet loss conditions, as the coder mismatch between the encoder and decoder are minimized. Simulation results show that this Robust GMM Kalman predictive coder performs better than other baseline GMM predictive coders with no increase in complexity. To the best of our knowledge, no previous work has specifically examined the design of GMM predictive coders for packet loss conditions.

关键词： Kalman filters predictive coding Robustness Decoding Performance loss predictive models Frequency Filtering Vector quantization Speech coding

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Adaptive Pixel-based Direction Oriented Fast Motion Estimation for predictive coding

Adaptive Pixel-based Direction Oriented Fast Motion Estimati...

引用

Picture coding Symposium, PCS

作者： Tushar Shinde Stanford University CA USA

ISBN: (纸本)9781665492584

This paper presents a novel Adaptive pixel-based direction-oriented fast motion estimation (APDME) method for lossless video compression. The traditional approach of block-based motion estimation suffers from two major issues: 1) the need to transmit side information such as motion vector overhead, and 2) incorrect motion estimation at object boundaries. The proposed method predicts motion on a pixel-by-pixel basis and addresses both the highlighted issues. In this pursuit, we present three contributions: 1) a novel target window design consisting of a spatially predicted pixel as a part of the search process, 2) initial MV prediction consisting of a global MV candidate, and 3) a novel direction oriented search patterns for faster search convergence. The proposed method achieves better entropy results and a significant reduction in the computations than pixel-based full search for varying motion content test sequences. Experimental results also suggest the proposed approach achieves superior entropy performance for fast and directional motion sequences with a computational edge over other competitive methods.

关键词： Performance evaluation Motion estimation Video compression predictive coding Entropy Encoding Convergence

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Memory Augmented Multi-Instance Contrastive predictive coding for Sequential Recommendation

Memory Augmented Multi-Instance Contrastive Predictive Codin...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Ruihong Qiu Zi Huang Hongzhi Yin School of Information Technology and Electrical Engineering The University of Queensland

ISBN: (纸本)9781665423991

The sequential recommendation aims to recommend items, such as products, songs and places, to users based on the sequential patterns of their historical records. Most existing sequential recommender models consider the next item prediction task as the training signal. Unfortunately, there are two essential challenges for these methods: (1) the long-term preference is difficult to capture, and (2) the supervision signal is too sparse to effectively train a model. In this paper, we propose a novel sequential recommendation framework to overcome these challenges based on a memory augmented multi-instance contrastive predictive coding scheme, denoted as MMInfoRec. The basic contrastive predictive coding (CPC) serves as encoders of sequences and items. The memory module is designed to augment the autoregressive prediction in CPC to enable a flexible and general representation of the encoded preference, which can improve the ability to capture the long-term preference. For effective training of the MMInfoRec model, a novel multi-instance noise contrastive estimation (MINCE) loss is proposed, using multiple positive samples, which offers effective exploitation of samples inside a mini-batch. The proposed MMInfoRec framework falls into the contrastive learning style, within which, however, a further finetuning step is not required given that its contrastive training task is well aligned with the target recommendation task. With extensive experiments on four benchmark datasets, MMInfoRec can outperform the state-of-the-art baselines.

关键词： Training Conferences Estimation Memory modules predictive coding predictive models Benchmark testing

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