分形语音处理

尽管分形在图像处理中已被广泛地采用，但是将分形技术与分形维数用于语音的表征与识别则是相对新的概念。本书介绍了开发用于语音及声频信号处理的基于分形技术所进行的研究成果。这一成果已经在诺基亚通讯公司和一些机构中得到了实际的商业应用。本书的作者M．阿尔一阿凯迪是英国De Monffort大学工程与技术学院的院长，     

A novel forecasting model for the Baltic dry index utilizing optimal squeezing

Marine transport has grown rapidly as the result of globalization and sustainable world growth rates. Shipping market risks and uncertainty have also grown and need to be mitigated with the development of a more reliable procedure to predict changes in freight rates. In this paper, we propose a new forecasting model and apply it to the Baltic Dry Index (BDI). Such a model compresses, in an optimal way, information from the past in order to predict freight rates. To develop the forecasting model, we deploy a basic set of predictors, add lags of the BDI and introduce additional variables, in applying Bayesian compressed regression (BCR), with two important innovations. First, we include transition functions in the predictive set to capture both smooth and abrupt changes in the time path of BDI; second, we do not estimate the parameters of the transition functions, but rather embed them in the random search procedure inherent in BCR. This allows all coefficients to evolve in a time-varying manner, while searching for the best predictors within the historical set of data. The new procedures predict the BDI with considerable success.