Time series segmentation is a fundamental component in the process of analyzing and mining time series data. Given a set of pattern templates, evolutionary computation is an appropriate tool to segment time series flexibly and effectively. In this paper, we propose a new distance measure based on pattern distance for fitness evaluation. Time sequence is represented by a series of perceptually i...

491 In this paper, an integrated data characteristic testing scheme is proposed for complex time series data exploration so as to select the most appropriate research methodology for complex time series modeling. Based on relationships across di®erent data characteristics, data characteristics of time series data are divided into two main categories: nature characteristics and pattern character...

Very large time series are increasingly available from an ever wider range of IoT-enabled sensors deployed in different environments. Significant insights can be gained by mining temporal patterns these series. Unlike traditional pattern mining, (TPM) adds event intervals into extracted patterns, making them more expressive at the expense increased and space complexities. Existing TPM methods e...

We address the problem of signal denoising and pattern recognition in processing batch-mode time-series data by combining linear time-invariant filters, orthogonal multiresolution representations, sparsity-based methods. propose a novel approach to designing higher-order zero-phase low-pass, high-pass, band-pass infinite impulse response filters as matrices, using spectral transformation state-...