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Archive for the ‘Markov Chain’ Category

[Attoparsec] has been building intriguing musical projects on his YouTube channel for a while and his latest is no exception. Dubbed simply as “Node Module”, it is a rack-mounted hardware-based Markov chain beat sequencer. Traditionally Markov chains are software state machines that transition between states with given probabilities, often learned from a training corpus. That same principle has been applied to hardware beat sequencing.

Each Node Module has a trigger input, four outputs each with a potentiometer, and a trigger out. [Attoparsec] has a wonderful explanation of all the different parts and theories that make up the module at the start of his video, but the basic operation is that a trigger input comes in and the potentiometers are read to determine the probabilities of each output. One is randomly selected and fired. As you can imagine, there are loops and even dead-end nodes and for some musical pieces there is a certain number of beats expected, so a clever reset signal can be sent to pull the chain back to the initial starting state at a regular interval. The results are interesting to listen to and even better to imagine all the possibilities.

The module itself is an Arduino-based custom PCB that is laid out quite cleanly. The BOM, code, and KiCad files are available on GitHub if you want to make one yourself. This isn’t the first instrument we’ve seen [Attoparsec] make, and we’re confident it won’t be the last.

Thanks [smellsofbikes] for sending this one in!

Aseen here, Bit by Jonghong Park at the University of the Arts Bremen is a beautiful visualization of how everything is linked together using the Markov chain principle. This installation uses an Arduino Mega for control, rotating arms that hold a pair of microswitches around coaxial gear-shaped cylinders.

In the sequence, one arm turns, then lobes on these “gears” that represent a two-bit number push the microswiches. This number is used to choose the following stepper to be turned in the sequence. The next selected arm then rotates in the same manner. This predictable cycle continues on and on clicking in a way that’s related, but not without careful observation.

The installation ‘bit’ represents a natural random process based on the principle of a Markov chain. Each machine consists of “information” engraved on the read head and an “event” caused by the operation of the motor. Machines are linked together based on a Markov chain algorithm to influence events, and eventually we can predict which of the four machines will move in the next turn. The movements of these four machines are shown as a random process, but in fact they are sequence of events. Like an invisible chain, all things and events in our world are connected.

Each of the four machines has its own state, which have been named ( 0,0 / 0,1 / 1,0 / 1,1 ), respectively. Each machine is equipped with a wooden read head with binary information on the surface and a microswitch to read the current state of the read head. The microswitch is connected to the stepper motors located in the center of the machine. A machine whose state is called moves the stepper motors by 1/240 of a degree. The microswitch turns on / off (1/0) along the surface of the read head each time the motor moves and calls the next machine corresponding to the state (2-Bit) of the current position of the read head. At this time, the machine corresponding to the measured state goes through the same process and calls another machine or itself.

These four machines symbolize another system separate from ours. We observe machines separate from the world as if we were watching computer simulations. The binary digits recorded in the read head are the smallest units of unspecified information possible, called bits. The bit, as the smallest particle that can make up the world and not simply as a digital recording unit, symbolizes the basis of this world. The things that we call noise, the information that we think of as meaningless, the information from which we cannot find the pattern, and the information that we cannot decode are called “chance”. When this information can be observed from outside our own world, we have proven through the Markov chain that all events are linked together.

The interplay concept is certainly interesting, and it’s pleasing to watch in the video below from a purely aesthetics point of view as well.



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