用增益精确值和归一化波形码书改进G.728

分析研究了增益、波形乘积码书结构的缺陷，设计了归一化波形码书和精确表示增益的LD-CELP方案。采用自适应预测和自适应量化对增益的精确值进行量化，在3bit和4bit自适应量化时比G．728固定量化增益分别提高0．5dB和6dB。采用4bit自适应量化和64波形码书比G.728SNR提高约1dB。将G．728综合滤波器由50阶减少到30阶，信噪比不变而算法复杂性降低约20%。     

低延迟码激励语音编码算法的最佳增益滤波器

该文采用加权L-S算法、有限记忆算法以及BP神经网络算法分别与G.728标准使用的Levinson_Durbin(L-D)方法进行5样点激励增益滤波方案比较测试,发现编码效果均好于G.728。其中加权L-S方法语音编码效果最好,其平均分段SNR高出G.728算法0.76dB。用该方法评价了16样点激励矢量增益滤波器和20样点激励矢量增益滤波器,加权L-S方法同样效果最佳。     

图象信号的自适应变系数DPCM编码

本文把图象信号作为一个高阶非稳马尔柯夫过程,提出一种自适应预测编码方案。预测系数依预测点附近区域的情况,进行自适应变化。用计算机进行模拟实验,当压缩到3.18bit/pel时,客观信噪比为44.78dB,加权信噪比为54.16dB,自适应变系数预测器的性能优于平面三点最佳线性预测器,可满足PAL制彩色电视亮度Y信号编码的传输标准要求。信道误码引起的误码图案依图象的内容而有变化,但扩散程度比固定预测要小。     

DBF-SAR系统1 bit量化的可行性分析

该文针对DBF-SAR系统数据率巨大的问题,研究了在低信噪比条件下1 bit量化的可行性。提出了两种信号处理方法：(1)回波1 bit量化;(2)回波和距离向匹配滤波器都1 bit量化。通过理论分析和仿真验证,1 bit量化的两种处理方法均能正确反映出目标位置及散射特性,不影响图像空间分辨率,但会产生虚假目标并抬升旁瓣,且虚假目标幅度随着回波信噪比的升高而增大。因此仅在单通道回波信噪比低于5 dB左右时使用1 bit量化才有意义。     

一种基于频移滤波器的混合信号盲恢复算法

针对单天线接收的频谱混叠的混合信号盲恢复问题,在频移滤波器结构上,提出了一种基于相关函数误差准则的自适应频移滤波信号盲恢复算法.该算法利用滤波器输出信号和参考信号以 及混合信号与参考信号之间的相关函数误差来调整自适应滤波器输出权值.分析了该算法的稳态性能.仿真结果表明:在信噪比大于-5 dB的条件下,该算法对混合...     

基于自适应窗长WD分析的伪码调相-载波调频复合引信信号的参数提取研究

该文研究了自适应窗长时频分析的理论及其实现方法,利用该方法对伪码体制复合引信信号进行脉冲内特征分析。这些信号具体包括伪码调相信号、伪码调相与正弦调频复合信号、伪码调相与线性调频复合信号。仿真结果表明,在信噪比为10dB时,利用自适应窗长时频分析技术,不但可以提取载频调制的特征信息,而且能够有效提取相位突变位置的特征信息。     

量化噪声对衰落信道下MRC合并信噪比的影响

文中主要研究瑞利平衰落信道下量化噪声对最大比合并(MRC)接收分集合并输出信噪比的影响.文中推导了量化噪声与信道噪声、信道参数之间的数学关系.仿真结果阐明量化对分集度几乎没有影响,只是使系统产生了固定的信噪比恶化.无论是1%中断率对应的信噪比,还是平均信噪比,1bit量化造成的损失约为2dB,而4bit量化的损失则在0.2～0.9dB左右.     

低信噪比下的语音端点检测算法研究

为了解决传统方法在强噪声环境下,语音检测性能急剧下降的缺陷,提高信号在低信噪比(0 db以下)语音端点检测的准确性,本文提出了一种将多窗谱估计谱减法和自适应子带能熵比相结合的检测算法.该算法利用增益因子可变的多窗谱估计谱减法对低信噪比信号进行降噪,提高其信号的信噪比,再将每帧信号分为若干个子带(其数量可自适应选择),提取每个子带能熵比参数进行端点检测.实验结果表明,当信噪比为-10 db时,信号检测准确性维持在95％左右.该方法能在低信噪比情况下,显著提高端点检测准确性和可靠性.     

采用量化器的自适应方块图象编码

本文提出了一种采用5 bit量化器的自适应方块图象编码方案。用此方案对“男孩和玩具”和“RMA测试卡”两幅图象中轮廓丰富的部分进行了计算机模拟实验。结果表明:信噪比均在34.45dB以上,平均比特率在3.12 bit/pel以下。比性能较好的一种简单的自适应方块图象编码方案信噪比提高1～3 dB,比特率下降0.3～0.6 bit/pel左右。主观实验表明,复原图象与原始图象相比,看不出明显的差别。     

基于改进LMS加BP神经网络的二相码旁瓣抑制

研究了BP神经网络在二相码旁瓣抑制中的应用,采用自适应学习速率梯度下降算法对网络进行训练,为了提高网络的抗噪声及多目标背景下的检测性能,训练的样本向量选取理想样本结合含噪声样本混合模式。此外,在将接收到的回波信号送入网络前,使其通过改进的自适应滤波器,以提高输入的信噪比。实验表明,对127位M码调相的不加噪声单目标回波,该算法能够使脉压输出的主旁瓣比达到60dB以上,并且在多目标及噪声环境下具有较好的性能。     

Comparison between adaptive search and bit allocation algorithmsfor image compression using vector quantization

This article discusses bit allocation and adaptive search algorithms for mean-residual vector quantization (MRVQ) and multistage vector quantization (MSVQ). The adaptive search algorithm uses a buffer and a distortion threshold function to control the bit rate that is assigned to each input vector. It achieves a constant rate for the entire image but variable bit rate for each vector in the image. For a given codebook and several bit rates, we compare the performance between the optimal bit allocation and adaptive search algorithms. The results show that the performance of the adaptive search algorithm is only 0.20-0.53 dB worse than that of the optimal bit allocation algorithm, but the complexity of the adaptive search algorithm is much less than that of the optimal bit allocation algorithm.     

Efficient codebooks for vector quantization image compression withan adaptive tree search algorithm

This paper discusses some algorithms to be used for the generation of an efficient and robust codebook for vector quantization (VQ). Some of the algorithms reduce the required codebook size by 4 or even 8 b to achieve the same level of performance as some of the popular techniques. This helps in greatly reducing the complexity of codebook generation and encoding. We also present a new adaptive tree search algorithm which improves the performance of any product VQ structure. Our results show an improvement of nearly 3 dB over the fixed rate search algorithm at a bit rate of 0.75 b/pixel     

Statistical Performance Analysis of an Interframe Encoder for Broadcast Television Signals

This paper desribes an objective evaluation for coding performance of an interframe encoder (NETEC-22H). Also described is the coding performance improvement by an adaptive bit sharing multiplexer (ABS-MUX) in which transmission bit rate is dynamically allocated to several channels. Measurements made for actual broadcast TV programs over a time of 36 h show that an SNR of higher than 50 dB unweighted is obtained by this coding equipment for 99 percent of the time for broadcast TV programs at the transmission bit rate of 30 Mbits/s and for 93 percent of the time at 20 Mbits/s. The residual 1 percent at 30 Mbits/s or 7 percent at 20 Mbits/s is transmitted with a slightly lower SNR. The picture quality difference between the 20 and 30 Mbit/s transmission is about 6 dB in SNR on the average. It is also shown that a three-channel ABS-MUX (20 Mbits/s per channel on the average) reduces probability of coarse quantization by a factor of 5-10 compared with the fixed bit rate transmission at 20 Mbits/s.     

Statistical Block Protection Coding for DPCM-AQF Speech

The statistical block protection coding scheme [2] for protecting DPCM encoded speech signals through noisy channels has been extended to accommodate DPCM-AQF encoded speech, where AQF stands for adaptive quantization with forward (explicit) transmission of step size. Signal-to-noise ratio (SNR) gains, typically 12 dB, have been achieved over a dynamic range> 20dB for a bit error rate (BER) of 1.4 percent and the SNR improvement is found to increase with BER. Perceptual improvements in decoded speech have a good correspondence with the gains in SNR. The penalty for this substantial enhancement in the performance of the DPCM-AQF system is an increase in transmission bit rate of 3.5 percent and encoding delay of 64 ms.     

时间相关信道的量化反馈算法研究

针对实际通信信道的时间相关特性,提出了一种基于有限状态向量量化（FSVQ）的信道量化算法。算法首先将信道划分为有限个状态,并为每一状态设计一个码本,码本用来量化从对应状态转移而来的信道。接收机只需要反馈信道向量在状态码本中的量化码字的序号。跟不考虑时间相关的向量量化算法相比,该算法能以相同的反馈负荷获得更高的性能。仿真结果表明,当信道相关系数为0.9,发射天线为6个,发射信噪比为0 dB的时候,该算法能提高接收信噪比性能1 dB。     

Rejection of an FH signal in a DS spread-spectrum system usingcomplex adaptive filters

The performance of a direct sequence QPSK spread-spectrum receiver using adaptive filters in the presence of frequency hopped interference is analyzed. The analysis includes both the adaptive prediction error filters and the adaptive transversal filters with two-sided taps. If the product of the instantaneous frequency offset Ω_l, between the jamming signal and the carrier of the spread-spectrum signal, and the sampling period Δ is 360° (Ω_l·Δ=360°), the filter gain is reduced to zero. The filter gain G highly depends on the filter adaptation rate μ. Depending on μ, G can vary from zero to more than 20 dB for a jammer/signal power ratio (J/S) of 20 dB. If Ω _l·Δ is small enough (⩽10°), the performance of the transversal filter is better than that of the prediction error filter, in the case when μ is small. For larger values of μ or Ω_l·Δ, these performances are approximately the same. Numerical results for the hopping sequence of the jamming signal are also presented. Besides the filter gain the analysis of the adaptation rate (time constant) filter misadjustment and the system bit error probability is also included     

Gaussian source coding with spherical codes

A fixed-rate shape-gain quantizer for the memoryless Gaussian source is proposed. The shape quantizer is constructed from wrapped spherical codes that map a sphere packing in ℝ^k-1 onto a sphere in ℝ^k, and the gain codebook is a globally optimal scalar quantizer. A wrapped Leech lattice shape quantizer is used to demonstrate a signal-to-quantization-noise ratio within 1 dB of the distortion-rate function for rates above 1 bit per sample, and an improvement over existing techniques of similar complexity. An asymptotic analysis of the tradeoff between gain quantization and shape quantization is also given     

用于图像编码的相关矢量量化研究

当相邻的图像块用矢量量化（ＶＱ）编码时可能出现编码地址相同的情况,尤其是在图像的平滑区。为了减少相邻块间编码地址的相关性,本文提出了一种相关矢量量化方案,采用相关码书与改进的自组织特征映射（ＩＳＯＦＭ）码书同时编码一个窗口内的四个邻域块,与无记忆类ＶＱ相比,对一幅典型的“Ｌｅｎｎａ”图象,编码过程中所需计算量减少一半,比特率减少４０％,由于在Ｋｏｈｏｎｅｎ自组织神经网络的训练过程中,对边缘类矢量采