simts (version 0.1.1)

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