A brief outline is as follows:
- Classical estimation and detection theory, discrete-time/vector models
- Representation of continuous-time stochastic processes
- Detection of signals, continuous-time waveforms
- Estimation of signal parameters
- Gaussian signals in AWGN
- Detection of random processes in noise
- Estimating the parameters of a random process
Two versions: The course is eligible for undergraduate, master and doctoral students. There will be two versions:
- 2E1434: An accelerated program (forskarförberedande) version, 5 cu's
- F2E5634: A Ph.D. student version, 8 cu's