共查询到18条相似文献,搜索用时 140 毫秒
1.
2.
3.
基于自组织特征映射的图像矢量量化研究 总被引:4,自引:0,他引:4
本文从自组织特征映射(SOFM)的基本思想出发,通过研究Kohonen网的输出节点在一维、二维和八维空间中不同排列方式,得到了相应的矢量量化(VQ)码书设计算法。研究表明SOFM具有许多优点:可以设计出具有规则结构的码书,相邻码矢量具有较强的相关性;网络输出节点的不同排列方式对矢量量化器性能有较大影响,通过选择合适的排列方式,设计出的矢量量化器具有良好的抗信道误码能力。实验表明基于SOFM算法的矢 相似文献
4.
根据通信信道中的数据聚集特点,结合自组织技术、竞争学习和监督学习算法提出了采用学习矢量量化网络实现非线性均衡器,并给出了应用。 相似文献
5.
一种快速模糊矢量量化图像编码算法 总被引:5,自引:3,他引:2
本文在学习矢量量化和模糊矢量量化算法的基础上,设计了一种新的训练矢量超球体收缩方案和码书学习公式,提出了一种快速模糊矢量量化算法。该算法具有对初始码书选取信赖性小,不会陷入局部最小和运算最小的优点。实验表明,FFVQ设计的图像码书性能与FVA算法相比,训练时间大大缩短,峰值信噪比也有改善。 相似文献
6.
一种设计语言信号波形矢量量化器的新算法 总被引:1,自引:0,他引:1
本文提出了波形矢量量化器码本的特征变量,对码本的分布特性进行了研究,提出了合理构造初始码本,快速训练码本和快速量化矢量的设计波形矢量量化器新算法,计算机模拟结果表明,新算法明显缩减了码本训练时间,提高了矢量量化的速度。 相似文献
7.
应用神经网络的图像分类矢量量化编码 总被引:3,自引:0,他引:3
矢量量化作为一种有效的图像数据压缩技术,越来越受到人们的重视。设计矢量量化器的经典算法LBG算法,由于运算复杂,从而限制了矢量量化的实用性。本文讨论了应用神经网络实现的基于边缘特征分类的矢量量化技术。它是根据人的视觉系统对图象的边缘的敏感性,应用模式识别技术,在对图像编码前,以边缘为特征对图像内容分类,然后再对每类进行矢量量化。除特征提取是采用离散余弦变换外,图像的分类和矢量量化都是由神经网络完成 相似文献
8.
矢量量化技术是一种既能高效压缩数码率,又能保持语音质量在编码方法,它不但能用于波形编码,而且能用于参数编码,本文主要论述了矢量量化在参数压缩编码中的应用,即应用模拟退火方法设计矢量量化器,对语音cep参数库进行压缩,通过语音倒谱参数库压缩前后,语音正确识别率听变化来评价所设计矢量量化器的性能,文章中提出了适用于语音倒谱参数的模拟退火时间表,对于所涉及的扰动范围,扰动次数方面主要参数进行了一定的探讨 相似文献
9.
10.
一种指数型模糊学习矢量量化图像编码算法 总被引:6,自引:0,他引:6
本文分析了模糊矢量量化(FVQ)图像编码的原理,提出了一种指数型模糊学习矢量量化算法(EFLVQ)。实验结果表明,该算法具有快速收敛性能,设计的图像码书峰值信噪比与FVQ算法相比也略有改善。 相似文献
11.
Channel-optimized vector quantization (COVQ) has proven to be an effective joint source-channel coding technique that makes the underlying quantizer robust to channel noise. Unfortunately, COVQ retains the high encoding complexity of the standard vector quantizer (VQ) for medium-to-high quantization dimensions and moderate-to-good channel conditions. A technique called sample adaptive product quantization (SAPQ) was recently introduced by Kim and Shroff to reduce the complexity of the VQ while achieving comparable distortions. In this letter, we generalize the design of SAPQ for the case of memoryless noisy channels by optimizing the quantizer with respect to both source and channel statistics. Numerical results demonstrate that the channel-optimized SAPQ (COSAPQ) achieves comparable performance to the COVQ (within 0.2 dB), while maintaining considerably lower encoding complexity (up to half of that of COVQ) and storage requirements. Robustness of the COSAPQ system against channel mismatch is also examined. 相似文献
12.
Wen-Jyi Hwang Faa-Jeng Lin Chin-Tsai Lin 《Communications Letters, IEEE》2000,4(12):408-410
A novel fuzzy clustering algorithm for the design of channel-optimized source coding systems is presented in this letter. The algorithm, termed fuzzy channel-optimized vector quantizer (FCOVQ) design algorithm, optimizes the vector quantizer (VQ) design using a fuzzy clustering process in which the index crossover probabilities imposed by a noisy channel are taken into account. The fuzzy clustering process effectively enhances the robustness of the performance of VQ to channel noise without reducing the quantization accuracy. Numerical results demonstrate that the FCOVQ algorithm outperforms existing VQ algorithms under noisy channel conditions for both Gauss-Markov sources and still image data 相似文献
13.
Phamdo N. Farvardin N. Moriya T. 《IEEE transactions on information theory / Professional Technical Group on Information Theory》1993,39(3):835-850
The large encoding complexity and sensitivity to channel errors of vector quantization (VQ) are discussed. The performance of two low-complexity VQs-the tree-structured VQ (TSVQ) and the multistage VQ (MSVQ)-when used over noisy channels are analyzed. An algorithm is developed for the design of channel-matched TSVQ (CM-TSVQ) and channel-matched MSVQ (CM-MSVQ) under the squared-error criterion. Extensive numerical results are given for the correlation coefficient 0.9. Comparisons with the ordinary TSVQ and MSVQ designed for the noiseless channel show substantial improvements when the channel is very noisy. The CM-MSVQ, which can be regarded as a block-structured combined source-channel coding scheme, is compared with a block-structured tandem source-channel coding scheme (with the same block length as the CM-MSVQ). For the Gauss-Markov source, the CM-MSVQ outperforms the tandem scheme in all cases that the authors have considered. It is demonstrated that the CM-MSVQ is fairly robust to channel mismatch 相似文献
14.
We design a channel optimized vector quantizer (COVQ) for symbol-by-symbol maximum a posteriori (MAP) hard-decision demodulated channels. The main objective is to exploit the non-uniformity of the indices representing the quantized source via the MAP decoder and iteratively optimize the overall discrete channel (at the symbol level) jointly with the quantizer. We consider memoryless Gaussian and Gauss-Markov sources transmitted over a binary phase-shift keying modulated Rayleigh fading channel. Our scheme has less encoding computational and storage complexity (particularly for noisy channel conditions) than both conventional and soft-decision COVQ systems, which use hard-decision and soft-decision maximum likelihood demodulation, respectively. Furthermore, it provides a notable signal-to-distortion ratio gain over the former system, and in some cases it matches or outperforms the latter one. 相似文献
15.
This article proposes a method to design a vector quantizer (VQ) for robust performance under noisy channel conditions. By re-optimizing the quantizer at progressively lower levels of assumed channel noise, the design is less susceptible to poor local optima. The method is applied to: (1) channel-optimized VQ design; and (2) index assignment for a source-optimized VQ. For both problems, we demonstrate substantial performance improvements over commonly used techniques 相似文献
16.
In this work, the design of a q-bit (scalar and vector) soft-decision demodulator for Gaussian channels with binary phase-shift keying modulation is investigated. The demodulator is used in conjunction with a soft-decision channel-optimized vector quantization (COVQ) system. The COVQ is constructed for an expanded (q>1) discrete channel consisting of the concatenation of the modulator, the Gaussian channel, and the demodulator. It is found that as the demodulator resolution q increases, the capacity of the expanded channel increases, resulting in an improvement of the COVQ performance. Consequently, the soft-decision demodulator is designed to maximize the capacity of the expanded channel. Three Gaussian channel models are considered as follows: (1) additive white Gaussian noise channels; (2) additive colored Gaussian noise channels; and (3) Gaussian channels with intersymbol interference. Comparisons are made with (a) hard-decision COVQ systems, (b) COVQ systems which utilize interleaving, and (c) an unquantized (q=∞) soft-decision decoder proposed by Skoglund and Hedelin (1999). It is shown that substantial improvements can be achieved over COVQ systems which utilize hard decision demodulation and/or channel interleaving. The performance of the proposed COVQ system is comparable with the system by Skoglund and Hedelin-though its computational complexity is substantially less 相似文献
17.
This work is concerned with the problem of designing robust, vector quantizer (VQ)-based communication systems for operation over time-varying Gaussian channels. Transmission energy allocation to VQ codeword bits, according to their error sensitivities, is a powerful tool for improving robustness to channel noise. The power of this technique can be further enhanced by appropriately combining it with index assignment methods. We pose the corresponding joint optimization problem and suggest a simple iterative algorithm for finding a locally optimal solution. The susceptibility of the solution to poor local minima is significantly reduced by an enhanced version of the algorithm which invokes the method of noisy channel relaxation whereby the VQ system is optimized while gradually decreasing the assumed level of channel noise. In a series of experiments, the resulting combined technique is shown to outperform standard pseudo-Gray coding by up to 3.5 dB and to exhibit graceful degradation at mismatched channel conditions. Finally, we extend these ideas to the case where both the transmitter and the receiver have information on the current state of a time-varying channel. The proposed method is based on switched encoding and adaptive decoding. Experimental results show that the proposed system achieves close to optimal performance 相似文献