Explanation: An even better approach is to quantize the difference, d(n) = x(n) –ax(n-1), w here a is a parameter selected to minimize the variance in d(n). This leads to the result that the optimum choice of a is 5. What is the quantity ax(n-1) is called?
A. Second-order predictor of x(n)
B. Zero-order predictor of x(n)
C. First-order predictor of x(n)
D. Third-order predictor of x(n)
Answer:A
Explanation: An even better approach is to quantize the difference, d(n) = x(n) –ax(n-1), w here a is a parameter selected to minimize the variance in d(n). This leads to the result that the optimum choice of a is 5. What is the quantity ax(n-1) is called?
A. Second-order predictor of x(n) B. Zero-order predictor of x(n) C. First-order predictor of x(n) D. Third-order predictor of x(n)
Explanation: In the equation d(n) = x(n) –ax(n-1), the quantity ax(n-1) is called a First-order predictor of x(n).