STATISTICAL SIGNAL PROCESSING AND COMPRESSIVE SENSING FOR INFERENCE PROBLEM (STACOS)
Modern statistical signal processing for solving an inference problem can be found at many systems designed to extract information, e.g., radar/sonar, speech, biomedicine, image analysis, robotics and communications. In years to come, massive connectivity is expected to be supported in the 5G and IoT networks. Thus, solving an inference problems by statistical signal processing is confronted with challenges of huge data processing, which then should not be handled by conventional methods. Furthermore, signal processing systems are expected to be more inteligent supported by learning capabilities.
In the summer school, we intend to give short courses on fundamental of statistical signal processing, machine learning and sparse/compressive sensing for inference problems, such as detection, estimation and classification. Furthermore, we will touch upon some very recent advances that are important in key applications in the future. The courses will include hands-on sessions and all topics deal with real-life signal processing problems. We will leave time for discussions on current trends and open problems.