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Lecture notes on the basic properties of systems, focusing on linearity, time-invariance, causality, and stability. It also covers the concept of convolution and impulse response in discrete systems. The notes include examples and proofs to help understand these concepts.
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What: Input x[n] → |SYSTEM| → y[n] output. Why: Design the system to filter input x[n]. DEF: A system is LINEAR if these two properties hold:
n=−∞ |h[n]|^ < L^ for some constant^ L where: Impulse δ[n] → |SYS| → h[n]=impulse response.
EX: A time-invariant system is observed to have these two responses: { 0 , 0 , 3 } → |SYS| → { 0 , 1 , 0 , 2 } and { 0 , 0 , 0 , 1 } → |SYS| → { 1 , 2 , 1 }. Prove: The system is nonlinear. Proof: By contradiction. Suppose the system is linear. But then: { 0 , 0 , 0 , 1 } → |SYS| → { 1 , 2 , 1 } implies { 0 , 0 , 3 } → |SYS| → { 3 , 6 , 3 } since we know it is time-invariant. Then { 0 , 0 , 3 } produces two outputs!
x[n] = { 3 , 1 , 4 , 6 } ⇔ x[n] = 3δ[n + 1] + 1δ[n] + 4δ[n − 1] + 6δ[n − 2]. Note: x[n] =
i x[i]δ[n^ −^ i] =^ x[n]^ ∗^ δ[n] (sifting property of impulse). Delay: x[n − D] is x[n] shifted right (later) if D > 0; left (earlier) if D < 0. Fold: x[−n] is x[n] flipped/folded/reversed around n = 0. Both: x[N − n] is x[−n] shifted right if N > 0 (since x[0] is now at n = N ). FOR LINEAR TIME-INVARIANT (LTI) SYSTEMS:
i x[i]δ[n^ −^ i]^ → |LT I| →^
i x[i]h[n^ −^ i]^ Linear:^ superposition.
i x[i]h[n^ −^ i] =^ h[n]^ ∗^ x[n]^ Convolution. Input x[n] into LTI system with no initial stored energy→output y[n]. PROPERTIES OF DISCRETE CONVOLUTION
i h[i]x[n^ −^ i] =^
h[n − i]x[i].
→ y[n] (parallel connection) Equivalent to: x[n] → |h 1 [n] + h 2 [n]| → y[n]. MA: y[n] = b 0 x[n] + b 1 x[n − 1] +... + bq x[n − q] (Moving Average) Huh? Present output=weighted average of q most recent inputs. Note: Equivalent to y[n] = b[n] ∗ x[n] where b[k] = bk, 0 ≤ k ≤ q. FIR: Finite Impulse Response ⇔ h[n] has finite duration. EX: Any MA system is also an FIR system, and vice-versa. IIR: Infinite Impulse Response ⇔ h[n] not finite duration. EX: h[n] = anu[n] = an^ for n ≥ 0 and |a| < 1 is stable and IIR.