The course discusses fundamentals of voice, data and video communications technology, differences between analog and digital transmission, and the migration to a converged digital/optical networks.the students should Study the components of networks, such as carrier switches, Routing, PBXs, T1 trunks, switched versus dedicated circuits, packet and wireless networks, and also the components of data networks such as modems, virtual circuits, hubs, switches and routers.

it describes the differences between all the various access methods including DSL, cable MODEMs, wireless (cellular, WiMax, Wi-Fi), T1 and Carrier Ethernet. it describes private voice network design alternatives using tie-lines, Centrex, virtual private networks (VPN) and hosted services. it lets students understanding PBX and IP-PBX features and voice traffic engineering, benefits, drawbacks and technology behind Voice over IP (VOIP) using IP PBXs, IP phones and Internet Telephony Service Providers (ITSP) and IPTV.

One advantage of digital circuits when compared to analog circuits is that signals represented digitally can be transmitted without degradation due to noise. For example, a continuous audio signal, transmitted as a sequence of 1s and 0s, can be reconstructed without error provided the noise picked up in transmission is not enough to prevent identification of the 1s and 0s. An hour of music can be stored on a compact disc as about 6 billion binary digits.
In a digital system, a more precise representation of a signal can be obtained by using more binary digits to represent it. While this requires more digital circuits to process the signals, each digit is handled by the same kind of hardware. In an analog system, the additional resolution requires fundamental improvements in the linearity and noise characteristics of each step of the signal chain. Digital circuits are sometimes more expensive, especially in small quantities.
Most useful digital systems must translate from continuous analog signals to discrete digital signals. This causes quantization errors. Quantization error can be reduced if the system stores enough digital data to represent the signal to the desired degree of fidelity. The Nyquist-Shannon sampling theorem provides an important guideline as to how much digital data is needed to accurately portray a given analog signal.
In some systems, if a single piece of digital data is lost or misinterpreted, the meaning of large blocks of related data can completely change. Because of the cliff effect, it can be difficult for users to tell if a particular system is right on the edge of failure, or if it can tolerate much more noise before failing.
Digital fragility can be reduced by designing a digital system for robustness. For example, a parity bit or other error management method can be inserted into the signal path. These schemes help the system detect errors, and then either correct the errors or at least ask for a new copy of the data. In a state-machine, the state transition logic can be designed to catch unused states and trigger a reset sequence or other error recovery routine.

The goal of this course is to evaluate any technical problem and taking decisions for the application of feedback control of the proper type for solving the problems.

To be able to design a stable feedback control system with one input and one output and optimized control characteristics.

Welcome to EAE&AT, it is a great opportunity to join our academy not only for building your future by gaining the scientific knowledge, but also to build balanced healthy social relations.

You will spend most of your day among your peers involving in social events, projects and other useful team work based activities.

In EAE&AT we are keen to build your personality regarding all the aspects since in real life scientific competency is not everything. You have to be able to work in a team and to be an active member. Consequently, you will become an active and successful leader.

Nowadays we are living in a world which depends on systems and every piece of information is represented by a signal. Engineers are dealing with systems and signals in all fields. The cutting edge technology is oriented to automation. Systems are controlled to behave autonomously with desired performance.

The importance of this course is to prepare the graduated engineers for what they are going to face in real life and give our students the advantage of getting familiar with modern technologies. 

The main topics of this course are:

  • Obtaining Laplace transforms of different functions and inverse Laplace transforms using partial fractions.
  • Using Matlab for obtaining partial fractions,  Laplace transforms, and inverse Laplace transform.
  • Getting the transfer function of a system described by a differential equation using Laplace Transform, drawing Block diagrams, and block diagrams reduction.
  • Getting the differential equation is of LTI systems, TF from the differential equations and using Simulink to solve differential equations.
  • Demonstrating the transient response of the 1st Order systems to unit impulse, unit step, and unit ramp input signals
  • Understanding the relation between the responses of LTI systems to the three input signals (impulse, unit, ramp) signals.
  • Demonstrating the transient response of the 2nd Order systems to unit impulse, unit step, and unit ramp input signals
  • PID
  • Steady State Error
  • Control system analysis and design using by the root locus method. 
  • Control system analysis and design using by the frequency response method

Welcome to EAE&AT, it is a great opportunity to join our academy not only for building your future by gaining the scientific knowledge, but also to build balanced healthy social relations.

You will spend most of your day among your peers involving in social events, projects and other useful team work based activities.

In EAE&AT we are keen to build your personality regarding all the aspects since in real life scientific competency is not everything. You have to be able to work in a team and to be an active member. Consequently, you will become an active and successful leader.

Nowadays we are living in a world which depends on systems and every piece of information is represented by a signal. Engineers are dealing with systems and signals in all fields. The cutting edge technology is oriented to automation. Systems are controlled to behave autonomously with desired performance.

The importance of this course is to prepare the graduated engineers for what they are going to face in real life and give our students the advantage of getting familiar with modern digital technologies.

The main topics of this course are:

  • z transform of elementary functions.
  • The important properties of z transform
  • The inverse z transform.
  • z transform method for solving difference equations.
  • Impulse sampling and data hold
  • Pulse Transfer functions
  • Realization of Digital Controllers
  • Stability analysis of closed loop systems in z plane
  • Transient and steady state response analysis.
  • Root Locus method
  • Frequency response method

 

Digital image processing is the use of computer algorithms to perform operations e.g. contrast enhancement, noise removal, smoothing etc. on digital images. Image processing applications include Remote sensing, Transmission and encoding, Machine/Robot vision, Color processing, Pattern recognition and Video processing.           

The aim of teaching this course is to introduce the students with:

  1. Image fundamentals and mathematical transforms necessary for image processing.
  2. Image enhancement techniques.
  3. Image restoration procedures.
  4. Image segmentation and compression procedures. 

References:

  1. Acharya, Tinku, and Ajoy K. Ray. Image processing: principles and applications. John Wiley & Sons, 2005.
  2. Gonzalez, Rafael C., and Richard E. Woods. "Digital image processing." (2002).