Random_Process_and_Nossdadise_Theory.pptx

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1. UNIT III: Random Process and Noise Theory An overview of Random Variables, Random Processes, and Noise Theory in communication systems.

2. Random Variables & Random Processes • Random Variables: Definition and types • Random Processes: Definition and classification • Applications in communication systems

3. Stationary and Ergodic Processes • Stationary Process: Strict-sense and Wide-sense • Ergodic Process: Definition and significance • Comparison of Stationary and Ergodic processes

4. Gaussian Process • Definition of Gaussian Process • Properties of Gaussian Processes • Applications in noise modeling

5. Transmission Through Linear Systems • Response of linear systems to random processes • Power spectral density considerations • Filtering effects on random signals

6. Noise Types • Shot Noise: Origin and characteristics • Thermal Noise: Johnson-Nyquist noise • White Noise: Flat spectral density • Narrow Band Noise: Band-limited noise

7. Noise Performance Metrics • Noise Equivalent Bandwidth: Definition and calculation • Noise Figure: Measuring system noise performance

8. Capture and Threshold Effect • Capture Effect: Impact on FM signals • Threshold Effect: Signal degradation in low SNR

9. Noise in AM • Impact of noise on Amplitude Modulation • Signal-to-noise ratio considerations • Noise suppression techniques

10. Conclusion • Summary of key concepts • Importance of noise analysis in communication systems • Applications in modern communication technologies