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A photodetector has a probability <math>p</math> of capturing each photon incident on it. A light source is exposed to the detector, and a million photons are captured. What is the ML estimate of the number of photons actually incident on it? | A photodetector has a probability <math>p</math> of capturing each photon incident on it. A light source is exposed to the detector, and a million photons are captured. What is the ML estimate of the number of photons actually incident on it? | ||
| − | == Problem 2: Imperfect | + | == Problem 2: Imperfect Radar == |
| + | A radar works by transmitting a pulse, and seeing if there is an echo. Ideally, an echo means object is present, and no echo means no object. However, some echoes might get lost, and others may be generated due to other surfaces. To improve accuracy, a radar transmits <math>n</math> pulses, where <math>n</math> is a fixed number, and sees how many echoes it gets. It then makes a decision based on this number. | ||
== Problem 3: Imperfect camera == | == Problem 3: Imperfect camera == | ||
== Problem 4: Imperfect camera == | == Problem 4: Imperfect camera == | ||
Revision as of 15:08, 5 November 2008
Contents
Instructions
Homework 9 can be downloaded here on the ECE 302 course website.
Problem 1: Imperfect camera
A photodetector has a probability $ p $ of capturing each photon incident on it. A light source is exposed to the detector, and a million photons are captured. What is the ML estimate of the number of photons actually incident on it?
Problem 2: Imperfect Radar
A radar works by transmitting a pulse, and seeing if there is an echo. Ideally, an echo means object is present, and no echo means no object. However, some echoes might get lost, and others may be generated due to other surfaces. To improve accuracy, a radar transmits $ n $ pulses, where $ n $ is a fixed number, and sees how many echoes it gets. It then makes a decision based on this number.
