The course briefly deals with fundamental stochastic processes such as Poisson, renewal, discrete-time Markov chain, continuous-time Markov chain, IBP, IPP, MMBP, MMPP, self-similar process. The course then covers various queueing systems and their applications such as Markovian BD queues, advanced Markovian models, M/G/1 priority queue, M/G/1 retrial queue, and M/G/1 queue with vacation.
Topics covered in this course include layered network architecture, open system interconnection (OSI), and various network protocols, such as Ethernet, Token Ring, FDDI, DQDB, X.25, Frame Relay, SMDS, Internet, telephone network, signaling network, and ATM network.
Recommend
Fundamental principles and mathematical bases underlying digital communication systems are introduced. Topics include MAP detection theory, optimum receivers, information theory, coding theory, and diversity techniques.
(Prerequisite: EE421)
Recommend
This is a graduate level course on data communication. The first half of the course involves an overview, data transmission, and data communication network. The latter half of the course involves internet protocol, internet service, and wireless internet.
Recommend
In this course, based on the fundamental concepts and knowledge addressed in EE210, we discuss advanced topics in probability and random processes for applications in engineering. Topics include algebra of sets, limit events, random vectors, convergence, correlation functions, independent increment processes, and compound processes. (Prerequisite: {EE210} or {Approval of the Instructor})
Recommend
Copyright ⓒ 2015 KAIST Electrical Engineering. All rights reserved. Made by PRESSCAT
Copyright ⓒ 2015 KAIST Electrical Engineering. All rights reserved. Made by PRESSCAT
Copyright ⓒ 2015 KAIST Electrical
Engineering. All rights reserved.
Made by PRESSCAT