Bland Statistics

Unfortunately, the analysis tool used to create a permutation of Super Mario has ultimately led me to a dead-end. While such analytic methods might help for basic applications such as chord progressions, they clearly don't work as well when applied to individual notes, since duration, velocity, and padding must also be taken into account.

If I had the time to develop a more comprehensive analysis tool that used more than just a first-order transitional Markov matrix, I might extract better results from this analytic method. I feel, however, that this would simply take too long. Such intense analysis would merit an entire thesis all of its own.

Markov Drumming Ideas

I need to create a list of statistical attributes that can be analyzed and linked to form a statistical Markov profile for drum styles. I also need to establish how attributes will be stored. Here are some ideas:

Format for statistical attribute: Node-(Trigger:Boolean Operator:Trigger...)=[Correlation],[Strength]

Examples
Snare-(Beat5:AND:CHatLast1)=26.73,2
Snare-(Beat5:AND:!CHatLast1:AND:ChatLast2)=53.9,4

The above attributes specify a few things. First, there is a 26.73% chance that a snare hit will directly follow a closed hi-hat hit on beat 5 (meaning the hi-hat hit falls on beat 4 and the snare hit falls on beat 5). Second, there is a 53.9% chance that a snare hit will follow a closed hi-hat hit by two beats on beat 5 provided that it does not directly follow a closed hi-hat hit (meaning the hi-hat hit falls on beat 3, beat 4 must not be filled by a hi-hat hit, and the snare hit falls on beat 5).

I think that these kinds of logical combinations will allow a thorough analysis of percussive styles.

Absolute Beat
The most basic trigger, this fires on a specific beat number.

Modulus Beat
Very similar to the absolute beat trigger, this trigger fires for each beat number computed modulus a certain divisor. In other words, it may fire every fourth beat, or every other beat, etc.

More on triggers later.