Dynamic Representation of Multivariate Time Series Data
提出一种通过计算机生成的动态图像和音乐来展示多元时间序列数据的方法，并用心理物理实验测量了该表示法可感知的相关性阈值。
Abstract In this article we describe a procedure for representing multivariate time series data by means of interactive, computer-generated dynamic imagery with computer-music accompaniment. This innovation conveys the novel insights that dynamic imagery can provide; yet, the imagery is developed from principles that make the representation useful when examined either statically or dynamically. This is because the development of the dynamic representation is guided by the same perceptual and technical principles used in making a motion picture. The particular implementation we describe is evaluated by a formal psychophysics experiment in which we measure the threshold correlation that can be perceived in our dynamic representation, and in each of three different types of graphical portrayals.