deriv_qn: Analytic D matrix for Quantization Noise (QN) Process

In simts: Time Series Analysis Tools

Analytic D matrix for Quantization Noise (QN) Process

Description

Obtain the first derivative of the Quantization Noise (QN) process.

Usage

deriv_qn(tau)

Arguments

tau	A vec containing the scales e.g. 2^{\tau}

Value

A matrix with the first column containing the partial derivative with respect to Q^2.

Process Haar WV First Derivative

Taking the derivative with respect to Q^2 yields:

\frac{\partial }{{\partial {Q^2}}}\nu _j^2\left( {{Q^2}} \right) = \frac{6}{{\tau _j^2}}

Author(s)

James Joseph Balamuta (JJB)

simts documentation built on Aug. 31, 2023, 5:07 p.m.