Question 1: Deterministic state flow¶
Let π = β be the state space. Let π : π β π be the deterministic state flow defined as π(π₯) = 2π₯ + 1.
Let
X_{k+1}(X_k) = \{x_{k+1} \in X \mid x_k \in X_k \text{ and } x_{k+1} = f(x_k) \}.
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Question 2: Nondeterministic state flow¶
Let π = β be the state space. Let π : π β pow(π) be the nondeterministic state flow defined as:
f(x) = \{x + d \in X \;|\; d \in [-1,1] \}.
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Let
X_{k+1}(X_k) = \{x_{k+1} \in X \mid x_k \in X_k \text{ and } x_{k+1} \in f(x_k) \}.
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Question 3: Nondeterministic temporal filtering¶
Consider the same setup as in the previous problem, but now include a sensor mapping β : π β π defined by:
y = \lfloor x + \tfrac{1}{2} \rfloor,
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in which βΒ·β denotes the floor function (equivalent to the floor function in Python).
Question 4: Discrete probability statements¶
Select ALL correct statements:
Question 5: More discrete probability statements¶
Select ALL correct statements:
Question 6: Gaussians and sampling¶
Let π β β be a collection of 10,000 distinct samples that have mean π and variance πΒ².
Make a set πβ = { π₯ β β β£ π₯ β 1 β π } by adding 1 to all of the samples. Make another set πβ = { π₯ β β β£ π₯ / 2 β π } by multiplying all of the samples by 2. Let πα΅’ and πα΅’Β² denote the mean and variance, respectively, of πα΅’ for π = 1, 2.
Question 7: Probabilistic filters¶
Select all correct statements:
Question 8: More probabilistic filters¶
Select all correct statements: