H.264变换编码与量化原理分析

详细分析了 H .2 64视频编码标准中的整数变换和量化过程。 H .2 64采用 4× 4整数变换 ,并将尺度调整融合在量化过程中 ,降低变换算法复杂度和减少乘法次数 ,相对于以前的编码标准更加有效     

中低速率语音波形编码

提出了一种波形编码的新方法，阐述了其编码原理。该编码算法简单，恢复的语音质量较好。由于利用了矢量量化技术，所以该编码速率较低。     

Sequential Decoding of Convolutional Codes for Rayleigh Fading Channels

The performance of sequential decoding of long constraint length convolutional codes is evaluated for Rayleigh fading channels. Sequential decoding is not practical below a certain theoretical signal-to-noise ratio, and these theoretical limits are calculated for a number of modulation methods and code rates. As an example, with BPSK modulation, soft decisions and code rate 1/2, the theoretical signal-to-noise ratio per information bit is 5.7 dB. Above this limit the bit error rate can be made arbitrarily small by increasing the constraint length at no significant complexity cost. Furthermore, it is shown that with carefully chosen quantization steps, 8 level uniform quantization gives a negligible loss also for sequential decoding on a Rayleigh fading channel. Simulation results using 8 level quantization correspond well with the theoretical performance bounds. Also, the performance on a correlated channel with finite interleaving has been obtained. With an interleaver depth of 50×50 and a normalized doppler frequency equal to 0.01 we are only 0.5 dB away from the performance with perfect interleaving. Finally, bit error rate results show this scheme to compete well with Turbo codes.     

基于神经网络的VQ图象编码

文章给出将神经网络与矢量量化相结合的两种编码方法，介绍了其原理和实现的算法。经计算机模拟表明，在比特率低于０．３ｂｐｐ时仍可得到高质量的编码图象。     

一种MPEG2视频编码的神经网络自适应量化算法

本文在ＭＰＥＧ２ＴＭ５建议我自适应量化策略的基础上，提出了一种ＭＰＥＧ２视频编码的神经网络自适应量化算法。     

基于小波变换的医学图象压缩编码

本文研究了医学图象小波变换系数的统计特征。根据医学图象的特点，提出了基于小波变换的医学图象编码方法。实验表明，这种方法具有较好的压缩编码性能，优于JPEG标准。同时，它支持逐次浮现式传输，从而能满足医学图象存储、通信、检索的需要。     

Tc trend in high-Tc superconductors

In our previous works, we have shown that most existing ceramic superconductors can be considered to be built of superconductor-semiconductor composite and we have estimated the change in phonon spectrum of the intrinsic superconductor unit if a semiconductor unit is attached to it. Moreover, the proximity effect under the size quantization condition has been examined in the superconductor-semiconductor composite. Each of the stated effects by itself could causeT _c enhancement in general as more semiconductor blocks are added to the system. We extend our study in this paper to analyze the combined actions of phonon spectral change and proximity effect without size quantization condition onT _c variation in members of the Tl₁ series of high-T _c superconductors. Our results indicate that an optimumT _c is obtained if the stated effects are included in the idealized unit cells of the superconductors made up of a superconductor-semiconductor array.     

Implementation of a vector quantization codebook design technique based on a competitive learning artificial neural network

We describe an implementation of a vector quantization codebook design algorithm based on the frequencysensitive competitive learning artificial neural network. The implementation, designed for use on high-performance computers, employs both multitasking and vectorization techniques. A C version of the algorithm tested on a CRAY Y-MP8/864 is discussed. We show how the implementation can be used to perform vector quantization, and demonstrate its use in compressing digital video image data. Two images are used, with various size codebooks, to test the performance of the implementation. The results show that the supercomputer techniques employed have significantly decreased the total execution time without affecting vector quantization performance.This work was supported by a Cray University Research Award and by NASA Lewis research grant number NAG3-1164.     

迭加与量化水印嵌入方案的比较及量化参数优化

分别研究了迭加法和量化法的隐蔽性和稳健性，并且提出了量化调制水印方案中的参数优化方法。对两类方法的分析比较表明，迭加法适用于在高频分量嵌入水印，而量化法适用于在低频分量嵌入水印。并以实验验证了这一结论。