What is mean by [1 -1] Filter? While studying about Wavelet Transform, I'm confused as why this is called a [1 -1] Filter , Here is what i'm talking about.


  In this hypothetical example the student does fairly well the first
  half of the     term then neglects his or her studies for the last
  half. Thus the exam scores     for the term were 80%, 80%, 80%, 80%,
  0%, 0%, 0%, and 0%*     We can tell the average of all the scores
  (40%) and when the scores “tanked”     after the 4th exam just by
  looking. Knowing the answer in advance, however,     is a good way to
  learn and to verify the wavelet transforms. Then we     can use them
  with confidence on real-world data where we can’t simply     “eyeball”
  the final values.
  
  We will now walk through the CWT process step by step using the
  simplest     of the wavelet filters on this example. We begin by
  comparing the humble Haar wavelet filter, [1 –1], with the data as
  shown


80 80 80 80 0 0 0 0


If We now keep subtracting each value from the next value we will eventually get,

[0, 0, 0, 80, 0, 0, 0]


Now If I want to stretch the Filter to three points i.e If the filter is stretched from [1 –1] to [1 0 –1].

How will I calculate these points as I did in case of two point Filter where i simply subtract each value from the next value ?
I have the same book as you. :-) 

The [1 -1] filter is a a simple differentiator, also known as, the Haar mother wavelet. You need to understand convolution to understand what he is saying. On the first level, you convolve your signal with [1 -1]. Then on the next level, you convole your signal with [1 0 -1], etc. That is all the CWT is doing. (Look at convolution first). If you understand that well, you can understand CWT very easily.