ENSS project

ENSS 300 (Signals & Systems) Lab Project

Instructors : Dr. Sabina Abdul Hadi Dr.Haitham Hani Abu Damis Done by: Aisha Bassam Naimi 2949

Start

1. Introduction

2.Key Objectives

INDEX

4.Task B

3. Task A

6.Conclusion

5. Task C

Introduction

This project delves into the intricate fields of signal processing and the application of MATLAB/Simulink. Our exploration centers on the analysis of signals and systems, presenting various challenges in evaluating signals across both frequency and time domains.

Key Objectives

• Signal Analysis: Understand the effects of changes in frequency and time on signals.

• Audio and Noisy Signals: Focus on the analysis and mitigation of noise interference in audio signals.

• Image Processing: Use filters to improve images and learn about their differences.

Task A

The Complete Code

Result and analysis:

Sampling Rate Determination: The sampling rate is determined by the highest frequency present in the function. Example: Given pairs (A, f), the highest frequency identified was 850Hz. Sampling Rule: The sampling frequency Fs should be greater than or equal to 2 Fmax (Fs>=2Fmx) ​Calculation: fs ≥ 2(850) fs ≥1700 Hz

F=1000Hz

F=10000Hz

F=1700Hz

Result and analysis:

Result and analysis:

Task B

Q. Use Simulink to design a block diagram to carry out the mixing procedure. Display the output of the transmitter in the time domain and in the frequency domain.

Spectrum Anlayzer

scope

TaskC

Filter1: Gaussian Purpose: Smoothing images and reducing noise. Operation: Applies a distribution through convolution with a Gaussian kernel. Benefits: 1-Reduces high-frequency noise. 2-Preserves edge details and significant features. 3-Alleviates random intensity fluctuations (noise). 4-Improves overall image quality.

Filter2: Disk Average filtersPurpose: Disk averaging filters are used in image processing to smooth images by averaging pixel values within a circular neighborhood around each pixel. Operation: The filter replaces each pixel's value with the average of the pixel values within the defined circular neighborhood, determined by the disk radius. Advantages: 1-Reduces noise and minor variations in the image. 2-Produces a smoother and more uniform appearance.

Result and analysis:

Conclusion

In conclusion, this project enhanced our understanding of signal processing in MATLAB/Simulink, focusing on noise reduction and image filtering techniques, improving both audio and image quality.