HOLY ANGEL UNIVERSITY College of Engineering & Architecture Department of Computer Engineering
University Vision, Mission, Goals and Objectives:
Mission Statement (VMG)
We, the academic community of Holy Angel University, declare ourselves to be a Catholic University. We dedicate ourselves to our core purpose, which is to provide accessible quality education that transforms students into persons of conscience, competence, and compassion. We commit ourselves to our vision of the University as a role-model catalyst for countryside development and one of the most influential, best managed Catholic universities in the Asia-Pacific region. We will be guided by our core values of Christ-centeredness, integrity, excellence, community, and societal responsibility. All these we shall do for the greater glory of God. LAUS DEO SEMPER! College Vision, Goals and Objectives: Vision
A center of excellence in engineering and architecture education imbued with Catholic mission and identity serving as a role-model catalyst for countryside development
Mission
To provide accessible quality engineering and architecture education leading to the development of conscientious, competent and compassionate professionals who continually contribute to the advancement of technology, preserve the environment, and improve life for countryside development.
Goals
The College of Engineering and Architecture is known for its curricular programs and services, research undertakings, and community involvement that are geared to produce competitive graduates:
- who are equipped with high impact educational practices for global employability and technopreneurial opportunities;
- whose performance in national licensure examinations and certifications is consistently above national passing rates and that falls within the 75th to 90th percentile ranks; and,
- who qualify for international licensure examinations, certifications, and professional recognitions;
Objectives
In its pursuit for academic excellence and to become an authentic instrument for countryside development, the College of Engineering and Architecture aims to achieve the following objectives:
1. To provide students with fundamental knowledge and skills in the technical and social disciplines so that they may develop a sound perspective for competent engineering and architecture practice;
2. To inculcate in the students the values and discipline necessary in developing them into socially responsible and globally competitive professionals;
3. To instill in the students a sense of social commitment through involvement in meaningful community projects and services;
4. To promote the development of a sustainable environment and the improvement of the quality of life by designing technology solutions beneficial to a dynamic world;
5. To adopt a faculty development program that is responsive to the continuing development and engagement of faculty in research, technopreneurship, community service and professional development activities both in the local and international context;
6. To implement a facility development program that promotes a continuing acquisition of state of the art facilities that are at par with leading engineering and architecture schools in the Asia Pacific region; and,
7. To sustain a strong partnership and linkage with institutions, industries, and professional organizations in both national and international levels.
Relationship of the Program Educational Objectives to the Vision-Mission of the University and the College of Engineering & Architecture:
Computer Engineering Program Educational Outcomes (PEOs):
Within a few years after graduation, our graduates of the Computer Engineering program are expected to have:
Vision-Mission
Christ-Centeredness
Integrity Excellence Community Societal
Responsibility
1. Practiced their profession
2. Shown a commitment to life-long learning
3. Manifested faithful stewardship
Relationship of the Computer Engineering Program Outcomes to the Program Educational Objectives:
Computer Engineering Student Outcomes (SOs): At the time of graduation, BS Computer Engineering program graduates should be able to:
PEOs
1 2 3
a) Apply knowledge of mathematics, physical sciences, and engineering sciences to the practice of Computer Engineering.
b) Design and conduct experiments, as well as to analyze and interpret data
c) Design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability, in accordance with standards
d) Function on multidisciplinary teams
e) Identify, formulate and solve engineering problems
f) Have an understanding of professional and ethical responsibility
g) Demonstrate and master the ability to listen, comprehend, speak, write and convey ideas clearly and effectively, in person and through electronic media to all audiences.
h) Have broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context
i) Recognition of the need for, and an ability to engage in life-long learning and to keep current of the development in the field
j) Have knowledge of contemporary issues
k) Use the techniques, skills, and modern engineering tools necessary for engineering practice.
l) Have knowledge and understanding of engineering and management principles as a member and leader in a team, to manage projects and in multidisciplinary environments.
COURSE SYLLABUS
Course Title: DIGITAL SIGNAL PROCESSING LABORATORY Course Code: DSPL
Course Credit: 1 unit Year Level: 4th year
Pre-requisite: Co-Req DSP Course Calendar: 2nd Semester, AY2016-2017
Course Description: DSP deals primarily with spectral analysis, convolution, correlation, Fourier transform, Discrete Fourier Transform (DFT), Fast Fourier Transform (FFT), z-transform, FIR/IIR Filtering, and applications of signal processing to speech and image.
Course Outcomes (COs): After completing this course, the students should be able to:
Relationship to the Program Outcomes:
a
b
c
d e f g h I j k l
1) Apply knowledge of mathematics appropriate in the analysis of signal spectra and signal processing.
D D D D D E D
2) Conduct experiments, analyze data and interpret the results obtained.
D D D D D E D
COURSE ORGANIZATION
Time Frame
Hours Course Outline Course
Outcomes Teaching Learning
Activities
Assessment Tools Resources
Week 1-3
9
1. Introduction to MATLAB
Evaluate Complex variables and expressions
Generate and Plot complex valued functions
Vectors and Matrices
Storing results and M-Files
Creation of Function in MATLAB
CO1 CO2
Laboratory Orientation
Course Orientation
Lecture on Introduction to MATLAB Programming with hands-on exercises
Visual Presentation
Individual Experiment
Short exercises prior to experiment
Oral Questioning
Checking of individual program output
Experiment Report
A1, combined with other course references
Week 4-6
9 2. Discrete Time Signal Generation
Periodic and Aperiodic sequence
Energy and Power
Generate unit step and unit sample sequences
Generate exponential sequence and sinusoidal sequences
Other Signal Waveform Generation Uniform random signal Square wave, sawtooth, and triangular waveforms
CO1 CO2
Short Lecture on the experiment
Individual Experiment
Checking of individual program output
Oral Questioning
Experiment Report
Major Exam
A1, combined with other course references
Week 3 3. Sampling of Continuous Time Signal CO1 Short Lecture on Checking of
7 Sampling Process in the time-domain Some Audio Effects
- Flip - Downsampling - Upsampling
CO2
the experiment Individual
Experiment
individual program output
Oral Questioning
Experiment Report
A1, combined with other course references
Week 8-10
9 4. Music Synthesis
CO1 CO2
Lecture on Music Synthesis and enhancement
Audio Visual Presentation
Group sharing Project
Project Presentation
Oral Questioning
A1, combined with other course references
Week 11
3 5. LTI System and Convolution CO1 CO2
Short Lecture on the experiment
Individual Experiment
Checking of individual program output
Experiment Report
Major Exam (Programming)
A1, combined with other course references
Week 12-14
9 6. Z-Transform and Discrete Fourier Transform
7. Filtering Concept 8. Fast Fourier Transform
Determine the frequency content of signals
FFT on simple speech recognition
CO1 CO2
Short Lecture on the experiment
Individual Experiment
Checking of individual program output
Oral Questioning
Experiment
A1, combined with other course references
Report
Week 15-18
12 9. Introduction to Digital Image Processing 10. Creating GUI for Signal Processing
CO1 CO2
Lecture on the experiment
Lecture with hands-on exercises on Creation of MATLAB GUI
Audio Visual Presentation
Discussion of Final project
Experiment Report
Project Presentation (This will serve as the Final Exam)
A1, combined with other course references
Course References:
A. Basic Readings
1) Mitra, Sanjit K. (2011). Digital Signal Processing: A Computer-Based Approach. McGraw-Hill Companies Inc.
B. Extended Readings (Books, Journals)
1) Cha, Philip D. and Molinder, John I. (2007). Fundamentals of Signals and Systems. Cambridge University Press 2) Gopalan, K. (2009). Introduction to Signal and Systems Analysis. Cengage Learning 3) Proakis, John G. (2000). Digital Signal Processing: Principles, Algorithms, and Applications. Pearson Education Asia Pte
Ltd. 4) Schilling, Robert J. (2012). Introduction to Digital Signal Processing using MATLAB. Cengage Learning
C. Web References 1) http://101science.com/dsp.htm 2) https://raspberry.kenet.or.ke/index.php/Digital_Signal_Processing 3) http://www.radio-electronics.com/info/rf-technology-design/digital-signal-processing/dsp-basics-tutorial.php
Course Requirements and Policies
1. 3 Major Exams(PRELIMS, MIDTERMS, FINALS) 2. Experiments 3. Research Paper or Project 4. Maximum Allowable Absences: 3 Aside from academic deficiency, other grounds for failing grade are: 1. Grave misconduct and/or cheating during examinations. 2. A failing academic standing and failure to take graded exams. 3. Unexcused absences of more than the maximum allowable absences per term.
Grading System:
Class Standing Experiments/Assignments (60%)
3 Major Exams (40%) TOTAL (100%)
CAMPUS++ COLLEGE ONLINE GRADING SYSTEM
Legend: (All Items in Percent) CSA Class Standing Average for All Performance Items (Cumulative) P Prelim Examination Score M Midterm Examination Score F Final Examination Score
MEA Major Exam Average PCA Prelim Computed Average MCA Midterm Computed Average FCA Final Computed Average Computation of Prelim Computed Average (PCA) CSA =
MEA = P PCA = (60%)(CSA) + (40%)(MEA) Computation of Midterm Computed Average (MCA) CSA =
MEA =
MCA = (60%)(CSA) + (40%)(MEA) Computation of Final Computed Average (FCA) CSA =
MEA =
FCA = (60%)(CSA) + (40%)(MEA)
Passing Percent Average: 60 Transmutation Table
6.00 Failure due to absences 8.00 Unauthorized or unreported withdrawal
Note: A student's Computed Average is a consolidation of Class Standing Percent Average and Major Exam Percent Average.
Date Revised: Date Effectivity: Prepared By: Checked By: Approved By:
June 2016 June 2016 Engr. Isabelita B. Pabustan ECE Faculty
Engr. Gerard C. Cortez Chairperson, CpE Department
Dr. Ma. Doris C. Bacamante Dean, College of Engineering and Architecture