The analysis of signals and the automation of repetitive tasks of recognition are ubiquitous in several applications such as bioengineering, biometrics, industrial inspection, agroindustry, artificial vision, bioacoustics and seismology. Professionals in those areas need advanced data and signal analysis techniques to understand better the nature of their objects of study and the interactions between the variables involved in their corresponding processes. In addition, pattern recognition techniques are able to provide them with advanced and reliable methods to automate classification or identification procedures as well as to assist them in complex decisions such as diagnoses and forecasts.
The research and education of the members of the Signal Processing and Recognition Group (formerly Control and Digital Signal Processing Group) reflect the above spectrum of applications. Our objectives are to study theoretical/applied Digital Signal Processing (DSP) and Pattern Recognition (PR) techniques for contributing to the state of the art in such areas and to study alternative data representations or data manipulations aimed to find underlying information and to understand statistical dependency among variables. Even though our study and research endeavors are focused on DSP and PR techniques, we must also deal with issues related to the implementation of the developed solutions; for example, scientific computing techniques and methods of algorithm analysis and design.
The research group on Signal Processing and Recognition includes researchers and students from the three Faculties of Universidad Nacional de Colombia Sede Manizales.