From bdb0d043093a239f088970139dda1f84364c79be Mon Sep 17 00:00:00 2001 From: tv3141 Date: Sat, 23 Sep 2017 10:12:01 +0100 Subject: [PATCH] Add missing 'g' --- 01-g-h-filter.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/01-g-h-filter.ipynb b/01-g-h-filter.ipynb index c5bfc33..f7e6db8 100644 --- a/01-g-h-filter.ipynb +++ b/01-g-h-filter.ipynb @@ -4464,7 +4464,7 @@ "source": [ "Here we can see the effects of ignoring the signal. We not only filter out noise, but legitimate changes in the signal as well. \n", "\n", - "Maybe we need a 'Goldilocks' filter, where is not too large, not too small, but just right? Well, not exactly. As alluded to earlier, different filters choose g and h in different ways depending on the mathematical properties of the problem. For example, the Benedict-Bordner filter was invented to minimize the transient error in this example, where $\\dot{x}$ makes a step jump. We will not discuss this filter in this book, but here are two plots chosen with different allowable pairs of g and h. This filter design minimizes transient errors for step jumps in $\\dot{x}$ at the cost of not being optimal for other types of changes in $\\dot{x}$." + "Maybe we need a 'Goldilocks' filter, where g is not too large, not too small, but just right? Well, not exactly. As alluded to earlier, different filters choose g and h in different ways depending on the mathematical properties of the problem. For example, the Benedict-Bordner filter was invented to minimize the transient error in this example, where $\\dot{x}$ makes a step jump. We will not discuss this filter in this book, but here are two plots chosen with different allowable pairs of g and h. This filter design minimizes transient errors for step jumps in $\\dot{x}$ at the cost of not being optimal for other types of changes in $\\dot{x}$." ] }, {