Subjects

Objectives and outcomes Introducing student to the theoretical and practical aspects of the spectral graph theory. Upon completion of the course, students have the knowledge about the spectral graph theory and are familiar with some … Read more

Basic concepts ofestimation. Kramer-Rao limit forthe variance ofestimators. The classictoolsforestimationof deterministicparameters.Minimum varianceestimators, sufficientstatistics, the best linearestimator, estimation bymethod of minimalsquares.Estimation ofnondeterministicparameters(Bayesianapproach). Prediction. Adaptiveinterference suppression. Optimum receiversfor systemswith intersymbol interference. Adaptivelinear equalization. Adaptiveequalizationwith feedback. Recursivealgorithms. Viterbialgorithm. … Read more

The convex and non-convex programming. Nonlinear programming (unconditional optimization; quadratic programming, convex programming, separable programming, integer programming). Dynamic programming. Multi-criteria optimization. Compromising programming. Abstract programming. The calculus of variations. The content of this course will … Read more

Introduction to the formal specification and verification of hardware: the context, design of circuits, errors and cycle of design. Formal verification, simulations, test vectors, test-benches, design-for-test and design-for-verification styles of writing code and verification based … Read more

The study ofthe physical layernetwork standardsIEEE802.11, 802.15, 802.16, BluetoothandHIPERLAN, UMTSandGPS.Specificsof the second layer. Adhocnetworksand specificity.Adhocmobilenetworks. Sensor networks. MAClayer foradhocnetworks. Routing inadhocnetworks.Savingenergy inadhocnetworks.The capacityof adhocnetworks, the quality of traffic inadhocnetworks.

Overview of digital modulation in space-time environment. Fundamentals of statistical signal processing and detection with application to assessment of channels and telecommunication signa ldetection and equalization. Overview of properties of channels with multiple paths and the concept of signal attenuation. Multi-antenna and MIMO systems. Iterative detection and decoding. The architecture of the receiver. The multiuser detection and turbo–codes. LDPC codes.

Linear subspaces. Characteristic values and characteristic vectors. The formulas for matrix inversion. Matrix. Kronecker product and Kronecker sum. Invariant subspaces. Vector norms and matrix norms. Singular value decomposition. Generalized inversion. Quadratic forms and definite matrices. … Read more

Objectives and outcomes Students are introduced to advanced techniques of natural language processing and extraction of useful knowledge from unstructured text. Students are able to select and apply an appropriate natural language processing technique to … Read more

Turing machines, primitive recursive functions, recursive functions, enumeration, universal functions, decidability, undecidability, partial decidability, recursive, and recursively enumerable sets, reducibility and degrees, recursion theorems. Computability, complexity classes, the relationship between complexity classes, reducing and completeness, … Read more

Periodogramsandcorrelograms. Non-parametricspectralanalysis. Methods ofbanksof filters. Parametric methodsfor linespectra. Rationalspectral methods. Spatialmethods. Processing ofsequences.MUSICalgorithm. Shape Recognition. Practicalapplication.