多缓冲机制下ADPCM解码算法适应性研究

文章对不同缓冲机制下ADPCM解码算法的运行条件进行了分析与对比,利用最小二乘法,提出关于ADPCM解码函数输入数据量与函数输入缓冲区长度的条件关系式,量化了不同缓冲机制对算法适应性的影响;针对实验环境的特点,改进了IMA ADPCM解码算法.研究结果表明,采用多缓冲机制能显著提高ADPCM算法的适应性;改进后的解码算法效率较原算法提高约75%.     

利用有限域上的伪辛几何构作一类Cartesian认证码

利用有限域上的伪辛几何构作一类Cartesian认证码，计算了新认证码的参数，并在假定按照等概率分布来选择编码规则下，计算了成功模仿攻击的概率和成功替换攻击的概率．     

多用户正交多级差分混沌键控通信系统

针对传统差分混沌键控(differential chaos shift keying, DCSK)采用多电平方式传输多进制信息导致误比特率(bit error rate, BER)高的缺点,提出一种多用户正交多级DCSK(multi-user orthogonal multi-level DCSK, MOM-DCSK)通信系统。该系统将传输的多进制信息映射为不同的传输系数,多个传输系数分别乘以对应的Walsh码后调制在信息承载信号上,并且通过不同的延时传输多用户信息。在加性高斯白噪声(additive white Gaussian noise, AWGN)信道和多径Rayleigh衰落信道中推导了系统的理论BER公式并进行了仿真分析。结果显示,该系统在传输多进制信息时拥有较好的误码性能,并且在多用户传输领域中有较好的实际应用价值。     

基于区间直觉模糊数ANP的体系贡献率计算方法

体系贡献率主要用于体系建设中度量装备对体系的贡献程度。为解决目前体系贡献率计算存在的一些问题,提出一种“任务–能力–指标–装备”的多层次装备指标体系结构。考虑了装备指标体系结构、网络分析法和区间直觉模糊数的特点,提出了一种基于区间直觉模糊数的网络分析法以得到更准确的体系贡献率。实验表明,该方法不仅能够解决体系贡献率计算公式现存的问题,而且与AHP(analytic hierarchy process)和ANP(analytic network process)相比,可以得到更准确的体系贡献率,为体系建设提供更有效的支持。     

引入微元法思想的混合测控资源联合调度方法

针对混合测控资源联合调度中存在的资源属性繁多、偏好差异大以及可能出现的调度弧段冲突等问题,借鉴单体制测控网调度研究中的任务需求描述方法,对混合测控任务需求的特点进行分析,给出其任务需求的规范化描述。以测控调度收益值最大为目标,建立混合资源联合调度模型;引入微元法思想,提出了可用弧段扩展复用方法,以此为基础提出了基于改进遗传算法的求解策略。仿真结果表明：所建模型和相应的解冲突算法能有效提高测控需求满足率和测控收益。     

Robust model rankings of forecasting performance

This paper investigates robust model rankings in out‐of‐sample, short‐horizon forecasting. We provide strong evidence that rolling window averaging consistently produces robust model rankings while improving the forecasting performance of both individual models and model averaging. The rolling window averaging outperforms the (ex post) “optimal” window forecasts in more than 50% of the times across all rolling windows.     

Exchange rate forecasting and the performance of currency portfolios

We examine the potential gains of using exchange rate forecast models and forecast combination methods in the management of currency portfolios for three exchange rates: the euro versus the US dollar, the British pound, and the Japanese yen. We use a battery of econometric specifications to evaluate whether optimal currency portfolios implied by trading strategies based on exchange rate forecasts outperform single currencies and the equally weighted portfolio. We assess the differences in profitability of optimal currency portfolios for different types of investor preferences, two trading strategies, mean squared error‐based composite forecasts, and different forecast horizons. Our results indicate that there are clear benefits of integrating exchange rate forecasts from state‐of‐the‐art econometric models in currency portfolios. These benefits vary across investor preferences and prediction horizons but are rather similar across trading strategies.     

Google Trends and the forecasting performance of exchange rate models

In this paper, we use Google Trends data for exchange rate forecasting in the context of a broad literature review that ties the exchange rate movements with macroeconomic fundamentals. The sample covers 11 OECD countries’ exchange rates for the period from January 2004 to June 2014. In out‐of‐sample forecasting of monthly returns on exchange rates, our findings indicate that the Google Trends search query data do a better job than the structural models in predicting the true direction of changes in nominal exchange rates. We also observed that Google Trends‐based forecasts are better at picking up the direction of the changes in the monthly nominal exchange rates after the Great Recession era (2008–2009). Based on the Clark and West inference procedure of equal predictive accuracy testing, we found that the relative performance of Google Trends‐based exchange rate predictions against the null of a random walk model is no worse than the purchasing power parity model. On the other hand, although the monetary model fundamentals could beat the random walk null only in one out of 11 currency pairs, with Google Trends predictors we found evidence of better performance for five currency pairs. We believe that these findings necessitate further research in this area to investigate the extravalue one can get from Google search query data.     

The US Dollar/Euro Exchange Rate: Structural Modeling and Forecasting During the Recent Financial Crises

The paper investigates the determinants of the US dollar/euro within the framework of the asset pricing theory of exchange rate determination, which posits that current exchange rate fluctuations are determined by the entire path of current and future revisions in expectations about fundamentals. In this perspective, we innovate by conditioning on Fama–French and Carhart risk factors, which directly measures changing market expectations about the economic outlook, on new financial condition indexes and macroeconomic variables. The macro‐finance augmented econometric model has a remarkable in‐sample and out‐of‐sample predictive ability, largely outperforming a standard autoregressive specification. We also document a stable relationship between the US dollar/euro Carhart momentum conditional correlation (CCW) and the euro area business cycle. CCW signals a progressive weakening in economic conditions since June 2014, consistent with the scattered recovery from the sovereign debt crisis and the new Greek solvency crisis exploded in late spring/early summer 2015. Copyright © 2016 John Wiley & Sons, Ltd.     

Differential space-time modulation in rapidly fading channels

Previously proposed differential modulation schemes for time-varying channels may not achieve the full transmit diversity and the maximum Doppler diversity simultaneously. Based on an existing basis expansion model, a new differential space-time code, which wisely combines interleaver/de-interleaver with traditonal space-time transmitting technique to overcome such limitation, .is presented. Two noncoherent differential decoders, named decision-feedback differential detector （DF-DD） and Viterbi-algorithmbased multiple-symbol-detection differential detector （ MSD-DD）, are also derived. We show that our design may recover data symbols with full antenna diversity and the maximum Doppler diversity at high signal-to-noise ratio. System performance is evaluated with simulations.