Call for Papers: Statistical Signal Extraction and Filtering

• Book ID: 104293435
• Publisher: Elsevier Science
• Year: 2004
• Tongue: English
• Weight: 85 KB
• Volume: 28
• Category: Article
• ISSN: 0165-1889
• DOI: 10.1016/s0165-1889(03)00140-4

✦ Synopsis

The need to extract signals and other components from time series is a requirement in many empirical sciences, including Medicine, Engineering, Economics and Climatology, to name but a few. Nowadays, a wide variety of methods are available, including Wiener--Kolmogorov Filtering, Kalman Filtering, Principal Components Analysis, and Wavelet Analysis. Some of the methods have been conceived in the time domain and others have originated in the frequency domain. A few of the methods may be interpreted equally in both domains. The majority demand skilful use of the computer for their successful implementation.

Given the variety of the available methods of Statistical Signal Extraction and Filtering, and given the diversity of the subject areas in which they are applied, there are plentiful opportunities for cross fertilisation and technology transfer. We therefore invite submissions for a special issue of Computational Statistics and Data Analysis devoted to this topic. We will consider papers addressing the use of computational and numerical methods for solving theoretical and practical issues associated with filtering and signal extraction algorithms, the impact of the techniques on the relevant subject areas, and specific applications involving computing and data analysis.

The papers submitted to the special issue should contain both computational and substantive (i.e. subject area) components. Authors who are uncertain of the suitability of their papers for the special issue should contact the special issue editors.