EC6002 ADVANCED DIGITAL SIGNAL PROCESSING  

EC6002 ADVANCED DIGITAL SIGNAL PROCESSING  | Important  Questions | Question bank | Syllabus | Model and Previous Question papers | Download PDF Exammain.com Important Questions is available for download in this page for EC6002 ADVANCED DIGITAL SIGNAL PROCESSING . Students can download the Important Questions in the PDF format or in Word format. Questions Bank and Previous year question papers also be available in this page  . Important Questions provided here are the Expected questions that are possible to be appeared in the upcoming exams. you can make use of the below questions and prepare for your exams. EC6002 ADVANCED DIGITAL SIGNAL PROCESSING  Important Questions . Download the Important Questions using the below link.

Subject Informations : 

University        :  Anna University
Department     :  B.E. ELECTRONICS AND COMMUNICATION ENGINEERING
Semester          :  06 th sem / ELECTIVE – I
Year                  :  03 rd year
Regulation       :  R2013
Subject Code   :  EC6002
Subject Name  :  ADVANCED DIGITAL SIGNAL PROCESSING

Are you Searching about Anna University Exams Important Questions ? Exammain.com is the right place to get all semester Anna University Important Questions Download PDF.

EC6002 ADVANCED DIGITAL SIGNAL PROCESSING  | Important  Questions
Syllabus	Click Here to Download
Part A Important Questions	Click Here to Download
Part B Important Questions	Click Here to Download  >>
Question Bank	Click Here to Download
Full Study Material	Click Here to Download
Other Subject Important Questions	Click Here to Download

OBJECTIVES :

 To bring out the concepts related to stationary and non-stationary random signals
 To emphasize the importance of true estimation of power spectral density
 To introduce the design of linear and adaptive systems for filtering and linear prediction
 To introduce the concept of wavelet transforms in the context of image processing

UNIT I DISCRETE-TIME RANDOM SIGNALS

Discrete random process – Ensemble averages, Stationary and ergodic processes, Autocorrelation
and Autocovariance properties and matrices, White noise, Power Spectral Density, Spectral
Factorization, Innovations Representation and Process, Filtering random processes, ARMA, AR and
MA processes.

UNIT II SPECTRUM ESTIMATION

Bias and Consistency, Periodogram, Modified periodogram, Blackman-Tukey method, Welch method Parametric methods of spectral estimation, Levinson-Durbin recursion

UNIT III LINEAR ESTIMATION AND PREDICTION

Forward and Backward linear prediction, Filtering – FIR Wiener filter- Filtering and linear prediction,
non-causal and causal IIR Wiener filters, Discrete Kalman filter.

UNIT IV ADAPTIVE FILTERS 

Principles of adaptive filter – FIR adaptive filter – Newton‟s Steepest descent algorithm – LMS
algorithm – Adaptive noise cancellation, Adaptive equalizer, Adaptive echo cancellers.

UNIT V WAVELET TRANSFORM

Multiresolution analysis, Continuous and discrete wavelet transform, Short Time Fourier Transform,
Application of wavelet transform, Cepstrum and H
omomorphic filtering.

TOTAL : 45 PERIODS

OUTCOMES:

Upon completion of the course, students will be able to :

 Explain the parametric methods for power spectrum estimation.
 Discuss adaptive filtering techniques using LMS algorithm and the applications of adaptive
filtering.
 Analyze the wavelet transforms.

Also check :

EC6002 ADVANCED DIGITAL SIGNAL PROCESSING  Notes – Click here to Download 

EC6002 ADVANCED DIGITAL SIGNAL PROCESSING  Questions Papers – Click here to Download 
EC6002 ADVANCED DIGITAL SIGNAL PROCESSING  2 marks with answers – Click here to Download 

Check Anna University –  Exam Result | Internal Mark    >>

Check Anna University Syllabus All Department – Click Here to Download  >>  

Note : Questions posted in this page should be made use only as a reference material. These Questions may or may not appear in the Semester Examination. Kindly Refer our Questions for preparing for your exams and also share it with your friends.

Mail your study material to exammain@gmail.com We will mention your name here.