Turbo／MAP编译码器中的交织器优化设计

讨论采用软输出迭代译交织级联卷积码（Ｔｕｒｂｏ码）编译码器中的交织器优化设计问题．从基于最大后验概率（ＭＡＰ）算法与迭代译码的Ｔｕｒｂｏ码编译码原理出发,给出交织器设计的一些基本方法并分析其特点;提出“保奇偶”的随机交织器设计方案,它能有效地改善某些以提高编码效率为目的的“删余截短”Ｔｕｒｂｏ码的纠错性能．通过计算机仿真得出一些Ｔｕｒｂｏ码在加性高斯白噪声信道中采用不同交织器时的误码率数据,分析了交织类型和交织深度的变化对Ｔｕｒｂｏ码纠错性能的影响．针对Ｔｕｒｂｏ码的特点提出了在卫星通信等应用中交织器设计的实用性结论．     

HDTV视频编码器的场景切换

当图象序列的帧与帧之间发生场景切换时,会影响视频编码器的编码质量．为提高高清晰度电视（ＨＤＴＶ）的视频编码器的编码质量,针对其采用的国际标准ＭＰＥＧ－２中ＧＯＰ的结构,提出按场景切换对齐的一种新的ＧＯＰ格式．软件模拟结果显示,ＭＳＥ值明显缩小,ＳＮＲ提高了３ｄＢ,效果较好．     

信号的角度调制原理

角度调制是用调制信号去控制载波信号角度(频率或相位)变化的一种信号变换方式,可以分为频率调制(FM)和相位调制(PM)。信号经过角度调制后,频谱结构将发生变化。     

A decision rule to minimize daily capital charges in forecasting value‐at‐risk

Under the Basel II Accord, banks and other authorized deposit‐taking institutions (ADIs) have to communicate their daily risk estimates to the monetary authorities at the beginning of the trading day, using a variety of value‐at‐risk (VaR) models to measure risk. Sometimes the risk estimates communicated using these models are too high, thereby leading to large capital requirements and high capital costs. At other times, the risk estimates are too low, leading to excessive violations, so that realized losses are above the estimated risk. In this paper we analyze the profit‐maximizing problem of an ADI subject to capital requirements under the Basel II Accord as ADIs have to choose an optimal VaR reporting strategy that minimizes daily capital charges. Accordingly, we suggest a dynamic communication and forecasting strategy that responds to violations in a discrete and instantaneous manner, while adapting more slowly in periods of no violations. We apply the proposed strategy to Standard & Poor's 500 Index and show there can be substantial savings in daily capital charges, while restricting the number of violations to within the Basel II penalty limits. Copyright © 2009 John Wiley & Sons, Ltd.     

水肥高效利用灌排系统调控面临的问题研究

通过调查我国水肥利用的现状,指出我国农业水利中干旱缺水、非点源污染、水资源利用率低下和灌排系统不配套等问题,提出灌区水肥高效利用需深入研究的热点问题,对探讨水肥高效利用和灌排系统管理理论,指导我国灌排系统精量调控,以最少的水肥投入量获取最佳的灌区产量和经济及生态环境效益,具有重要意义.     

一种适用于高阶QAM载波恢复的改进型稳定性算法

本文提出了一种结合频率相位载波恢复的数字QAM接收系统,将非零均值引入到Stop—and—Go控制器中,有效地解决了稳定状态的误差偏移较大的问题。仿真结果表明系统在15dB信噪比时,采用载波恢复电路只需7500个符号周期即可捕获达到6％符号率的频偏和30。的相偏,同时其稳态相位抖动亦显著减少到0．07。     

A Neuro‐wavelet Model for the Short‐Term Forecasting of High‐Frequency Time Series of Stock Returns

We propose a wavelet neural network (neuro‐wavelet) model for the short‐term forecast of stock returns from high‐frequency financial data. The proposed hybrid model combines the capability of wavelets and neural networks to capture non‐stationary nonlinear attributes embedded in financial time series. A comparison study was performed on the predictive power of two econometric models and four recurrent neural network topologies. Several statistical measures were applied to the predictions and standard errors to evaluate the performance of all models. A Jordan net that used as input the coefficients resulting from a non‐decimated wavelet‐based multi‐resolution decomposition of an exogenous signal showed a consistent superior forecasting performance. Reasonable forecasting accuracy for the one‐, three‐ and five step‐ahead horizons was achieved by the proposed model. The procedure used to build the neuro‐wavelet model is reusable and can be applied to any high‐frequency financial series to specify the model characteristics associated with that particular series. Copyright © 2013 John Wiley & Sons, Ltd.     

危机信息传播有效性的离散化不确定性评估模型

以科学评估危机信息传播有效性为目标,结合国内外前沿文献对危机信息传播的影响因素和传播过程的不确定性进行了分析论述。分析认为,危机信息传播有效性是一个不确定性概念,是模糊性与随机性的统一;其评估问题也需要从模糊性与随机性两个方面结合进行考虑。应用模糊随机理论,构建了危机信息传播有效性的离散化评估模型,并给出了隶属函数的确定方法。这是对危机信息传播有效性评估理论与方法的拓展,为危机信息传播有效性的定量研究提供了思路。     

便携式发电机整流稳压电源设计

针对便携式发电机的特殊要求,给出了一种能够满足宽压和宽频输入的整流电源的设计方案。为了使系统获得良好的稳态和动态性能,在系统中加入了反馈控制和前馈控制相结合的复合控制。实验证明,该系统不仅能够适应宽压和宽频输入,而且在输入电压和频率大幅度变化时仍能稳定可靠地工作。     

An ensemble of LSTM neural networks for high‐frequency stock market classification

We propose an ensemble of long–short‐term memory (LSTM) neural networks for intraday stock predictions, using a large variety of technical analysis indicators as network inputs. The proposed ensemble operates in an online way, weighting the individual models proportionally to their recent performance, which allows us to deal with possible nonstationarities in an innovative way. The performance of the models is measured by area under the curve of the receiver operating characteristic. We evaluate the predictive power of our model on several US large‐cap stocks and benchmark it against lasso and ridge logistic classifiers. The proposed model is found to perform better than the benchmark models or equally weighted ensembles.