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Functional Quantization-Based Data Compression in Seismic Acquisition (vol 44, pg 2151, 2019)

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2019年第3期44卷 2853-2853页

作者： Khan, Hamood Ur Rehman Zummo, Salam A. King Fahd Univ Petr & Minerals Elect Engn Dept Dhahran 31261 Saudi Arabia

The trend in seismic acquisition is geared toward high geophone densities. Future node densities are expected to be on the order of 1M nodes, leading to a huge aggregate data rate in the geophone array and requiring the use of some form of signal compression. This work presents a family of signal compression algorithms based on vector quantization and its transposition to the infinite-dimensional case—functional quantization (FQ). Using FQ, we quantize the entire sample path of the seismic waveform in a target function space, instead of quantizing individual samples. The polynomial design and computational complexity afforded by FQ allow for online training of codebooks where the statistics of the seismic wavefield may be changing. An efficient algorithm for the construction of a functional quantizer is given. It is based on Monte Carlo simulation to circumvent the curse of high dimensionality and avoids explicit construction of Voronoi regions to tessellate the function space of interest. In the sequel, we augment our basic FQ architecture with three different VQ techniques in the literature. The augmentation yields hybridized FQ strategies. These hybrid quantization algorithms are: (1) FQ-classified VQ, (2) FQ-residual/multistage VQ and (3) FQ-recursive VQ. The joint quantizers are obtained by replacing regular VQ codebooks in these hybrid quantizers by their FQ equivalents. Simulation results show that the FQ combined with these different VQ techniques performs better in the rate–distortion sense than either FQ alone or the aforementioned VQ techniques in isolation.

关键词： Centroidal Voronoi Tessellation Functional quantization Infinite-dimensional quantization lbg algorithm Residual vector quantization Vector quantization

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THE ARTIFICIAL BEE COLONY algorithm FOR VECTOR QUANTIZATION IN IMAGE COMPRESSION

THE ARTIFICIAL BEE COLONY ALGORITHM FOR VECTOR QUANTIZATION ...

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4th IEEE International Conference on Broadband Network and Multimedia Technology (IEEE IC-BNMT 2011)

作者： Horng, Ming-Huwi Jiang, Ting-Wei Natl PingTung Inst Commerce Dept Comp Sci & Informat Engn Pingtung Taiwan

ISBN: (纸本)9781612841564

The vector quantization was a powerful technique in image compression. The widely used method _ such as the Linde-Buzo-Gray (lbg) algorithm always generated local optimal codebook. Recently, particle swarm optimization was adapted to obtain the near-global optimal codebook of vector quantization. The alterative method called the quantum particle swami optimization was developed to improve the results of original PSO algorithm. The honey bee mating optimization was used to develop the algorithm for vector: quantization. In this paper, we proposed a new method based on the artificial bee colony (ABC) algorithm to construct the codebook of vector quantization. The proposed method use lbg method as the initial of ABC algorithm to develop the VQ algorithm. This method is called ABClbg algorithm. The ABC-lbg algorithm is compared with four algorithms described above. Experimental results showed that the ABC-lbg algorithm-is more-reliable and the reconstructed images get higher quality compared to other methods.

关键词： Vector quantization lbg algorithm Particle swarm optimization Quantum particle swarm optimization Honey bee mating optimization Artificial bee colony algorithm

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Identification of Correlation between Blood Relations Using Speech Signal

Identification of Correlation between Blood Relations Using ...

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IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES)

作者： Padmini, Palli Tripathi, Shikha Bhowmick, Kaustav Amrita Univ Dept Elect & Commun Engn Bengaluru India

ISBN: (纸本)9781538638644

This paper presents a study of how speech features have comparable parameters amongst blood relations. Mel Frequency Cepstral Coefficients (MFCC) has been used for extracting the features of input speech signal, along with vector quantization through modified k-means lbg (Linde, Buzo, and Gray) algorithm are implemented to analyse and estimate the similarity to perform related studies. The study is concentrated on database using 12 families from which voice databases were collected from all users, of different age groups, of each family. The Finding of the study shows a high correlation (Max similar to 95%) between similar genders of the family and low correlation (Min similar to 80%) between dissimilar genders of the family.

关键词： Gayathri Mantra Vector Quantization lbg algorithm MFCC Matlab

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Precoder Quantization vs Channel Quantization in Interference Channel with Limited Feedback 23

Precoder Quantization vs Channel Quantization in Interferenc...

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23rd National Conference on Communications (NCC)

作者： Garg, Navneet Sharma, Govind Indian Inst Technol Kanpur 208016 Uttar Pradesh India

ISBN: (纸本)9781509053568

In this paper, we compare the precoder and channel feedback in interference channel (IC) when interference alignment (IA) is used. In literature, the channel direction has been quantized and fed back in IC. Here, we consider the precoder quantization and feedback (PQFB) in IC, and seek its benefits over channel feedback. The involvement of IA (where the alignment is sensitive to channel changes) and comparison of required time slots, codebook size and feedback bit rate, show that PQFB is a better choice. The theoretical rate loss for both schemes show that precoder feedback gives less loss in sum rate as compared to channel direction feedback. These results are verified with simulations.

关键词： Interference channel limited feedback precoder feedback channel feedback lbg algorithm chordal distance interference alignment rate loss upper bound

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A new initial codebook algorithm for learning vector quantization

A new initial codebook algorithm for learning vector quantiz...

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IEEE International Conference on Communications (ICC 2007)

作者： Li, Hongsong Xu, Baohua Beijing Normal Univ Coll Informat Sci & Technol Beijing 100875 Peoples R China

ISBN: (纸本)9781424403523

In this paper, a new sorting initial codebook algorithm for, learning vector quantization (LVQ) based upon self-organizing feature maps (SOM) has been proposed. The basic idea is that the similar codewords are put together in the initial codebook. To improve the performance of SOM algorithm, we have presented a new winning self-organizing feature maps (WSOM). Experimental results for image VQ show that the average PSNR improvement of this new initial codebook algorithm is 0.7dB compared to the common random sampling algorithm, and the WSOM algorithm has better coding performance than the lbg and SOM algorithm.

关键词： self-organizing feature maps learning vector quantization lbg algorithm image coding

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Design and Implementation Issues of Parallel Vector Quantization in FPGA for Real Time Image Compression

Design and Implementation Issues of Parallel Vector Quantiza...

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International Conference on Intelligent Computing and Information Science

作者： Rasane, Krupa R. Kunte, Srinivasa Rao R. KLESCET Dept Elect & Commun Engn Belgaum Karnataka India JNNCE Shivamogga Karnataka India

ISBN: (纸本)9783642181337

In this paper a 4 codebook, Vector Quantization (VQ) core is implemented on FPGA (Field Programmable Gate Array). The proposed design has certain advantages over the earlier architecture in the form of design reuse of VQ core to build a large VQ system. The proposed core aims at increased compressing speed, modular design for design flexibility, easy reconfigurability. Modularity helps in flexile design changes for VQ with different codebook sizes and hence controls the recovered image quality. In general, the new VQ core, meets the specific and challenging needs of a single functioned, tightly constrained real time VQ encoder. The synthesis results show that a speed up of 5 is achieved. Experiments and analyses indicate that our design can satisfy the performance requirements of 30 image frames per sec for a real time image processing. The proposed VQ requires more memory and implements VQ encoder with codebook size which are in multiples of 4.

关键词： Vector Quantization Image compression lbg algorithm Image encoder VLSI pipelining FPGA

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An Intrusion Detection Technique based on Multi Dimension VQ

An Intrusion Detection Technique based on Multi Dimension VQ

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IEEE International Conference on Electronics, Communications and Control (ICECC)

作者： Wang, Xiaolei Hu, Jinping Liu, Fen Tang, Hongbo Natl Digital Switching Syst Engn & Technol Res Ct Zhengzhou Peoples R China

ISBN: (纸本)9781457703218

This paper applied the theory of vector quantization, and changed the process of class into the process of cell segmenting, then proposed a new intrusion detection technique which need no training sample and has high stability. The simulation based on the kddcup99 data set and the contrast with other mainstream technique proved that it has high probability of detection and high stability.

关键词： component intrusion detection vector quantization lbg algorithm class

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Hearing Environment Recognition in Hearing Aids 12

Hearing Environment Recognition in Hearing Aids

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12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Zeng, Weihao Liu, Ming Harbin Inst Technol Shenzhen Grad Sch Key Lab IOT Terminal Pivotal Technol Shenzhen Peoples R China

ISBN: (纸本)9781467376822

The hearing environment recognition algorithm is one of the core algorithms of the modern digital hearing aids. It can recognize the quiet, noisy and musical environment under a variety of scenarios, such as street, train or restaurant scene in noise environment. It then adjusts the parameters of other hearing aids algorithms according to different audio environment. This paper presents a method to improve the training algorithm of Gaussian mixture models(GMMs), which uses fusion lbg clustering algorithm and annealing algorithm to initialize the value of GMM parameter means mu, instead of initializing it randomly in traditional way. The method can improve recognition accuracy by optimizing the GMM parameters. The experimental result demonstrates that the accuracy rate of the traditional GMMs algorithm is about 77%, while that of the method we proposed is about 85%. In the end, we continue to explore the influence of the selection of the MFCC features and Gaussian mixture numbers on the recognition rate.

关键词： Hearing environment recognition Hearing aids GMMs lbg algorithm Annealing algorithm MFCC features

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Honey Bee Mating Optimization Vector Quantization Scheme in Image Compression

Honey Bee Mating Optimization Vector Quantization Scheme in ...

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International Conference on Artificial Intelligence and Computational Intelligence

作者： Horng, Ming-Huwi Natl Pingtung Inst Commerce Dept Informat Engn & Comp Sci Pingtung Taiwan

ISBN: (纸本)9783642052521

The vector quantization is a powerful technique in the applications of digital image compression. The traditionally widely used method such as the Linde-Buzo-Gray (lbg) algorithm always generated local optimal codebook. Recently, particle swarm optimization (PSO) is adapted to obtain the near-global optimal codebook of vector quantization. In this paper, we applied a new swarm algorithm, honey bee mating optimization, to construct the codebook of vector quantization. The proposed method is called the honey bee mating optimization based lbg (HBMO-lbg) algorithm. The results were compared with the other two methods that are lbg and PSO-lbg algorithms. Experimental results showed that the proposed HBMO-lbg algorithm is more reliable and the reconstructed images get higher quality than those generated form the other three methods.

关键词： Vector quantization lbg algorithm Particle swarm optimization Quantum particle swarm optimization Honey bee mating optimization

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Speaker Recognition using MFCC, shifted MFCC with Vector Quantization and Fuzzy

Speaker Recognition using MFCC, shifted MFCC with Vector Qua...

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International Conference on Soft Computing Techniques and Implementations (ICSCTI)

作者： Bansal, Priyanka Imam, Syed Akhtar Bharti, Roma Jamia Millia Islamia New Delhi India Manav Rachna Int Univ Faridabad India

ISBN: (纸本)9781467367929

In the range of biometric we consider the variability of discourse flag because of the vicinity of clam or which impressively corrupts the productivity of ASR in genuine ecological condition. Speaker-vocal attributes exist in discourse signals and because of distinctive resonances of diverse speakers speaker acknowledgment framework checks the speaker. These distinctions can be misused by extricating element vectors like Mel-Frequency Cepstral Coefficient (MFCCs) from the discourse signal. In this paper we have utilized MFCC and Shifted MFCC with Vector Quantization and fuzzy demonstrating strategies correspondingly to enhance the execution of ASR even in boisterous environment with the assistance of redesigned discourse data which are available at high recurrence in otherworldly area. The mix of fuzzy demonstrating and shifted MFCC makes an in number total calculation which has the sensibly high vigour to clamour. In exploratory results, we have discovered 10-20% upgraded precision even at 5-8dB SNR in the vicinity of music foundation, boisterous natural condition furthermore in the vicinity of repetitive sound.

关键词： Automatic Speaker Recognition(ASR) MFCC (mel frequency cepstral coefficient) Vector Quantization lbg algorithm fuzzy

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