Pinned Repositories
8Puzzle
absence.io
AgreenaChallenge
AgreenaChallenge2
CellularAutomata
a cellular automata sequencer for rhythm generation
cellularUtil
Parse and resize a cellular automata lib that is referenced on wikipidia
collinear
Computer vision involves analyzing patterns in visual images and reconstructing the real-world objects that produced them. The process is often broken up into two phases: feature detection and pattern recognition. Feature detection involves selecting important features of the image; pattern recognition involves discovering patterns in the features. We will investigate a particularly clean pattern recognition problem involving points and line segments. This kind of pattern recognition arises in many other applications such as statistical data analysis.
euclidean
A simple euclidean rhythm generator external for Max
genetic
A Max/Msp object to find a parameter set based on the genetic algorithm developed with the min sdk
Markov-midi
prototype for a markov midi processing system written in Max Msp and Javascript
concancon's Repositories
concancon/cellularUtil
Parse and resize a cellular automata lib that is referenced on wikipidia
concancon/DX7
Dx7 Implementation in Max/Msp based on the tutorial series from Really Useful Plugins
concancon/euclidean
A simple euclidean rhythm generator external for Max
concancon/genetic
A Max/Msp object to find a parameter set based on the genetic algorithm developed with the min sdk
concancon/Markov-midi
prototype for a markov midi processing system written in Max Msp and Javascript
concancon/8Puzzle
concancon/absence.io
concancon/AgreenaChallenge
concancon/AgreenaChallenge2
concancon/CellularAutomata
a cellular automata sequencer for rhythm generation
concancon/collinear
Computer vision involves analyzing patterns in visual images and reconstructing the real-world objects that produced them. The process is often broken up into two phases: feature detection and pattern recognition. Feature detection involves selecting important features of the image; pattern recognition involves discovering patterns in the features. We will investigate a particularly clean pattern recognition problem involving points and line segments. This kind of pattern recognition arises in many other applications such as statistical data analysis.
concancon/ComponentBasedDevelopment
RESTful Java EE Webservice developed using pair programming with @noeljns
concancon/interview-task
concancon/Markov-N-order
higher order Markov Chains
concancon/MultilayeredMarkov
concancon/Deque
Deque with the following performance requirements: The implementation must support each deque operation (including construction) in constant worst-case time. A deque containing n items must use at most 48n + 192 bytes of memory. Additionally, your iterator implementation must support each operation (including construction) in constant worst-case time.
concancon/destructuring-performance-measurement
Compare the performance of destructuring inside a reduce loop
concancon/EOSSite
concancon/euclid_cpp
C++ version of euclidean~external developed with the min sdk
concancon/gen_rhythm
Modules for rhythmic ratcheting in gen
concancon/Lock-Free-Queue
concancon/Markov-Poly
concancon/mock
A mocked/stubbed library for linking unit tests of Max externals built with the Min-DevKit.
concancon/OpenGL
Repository to explore learn OpenGL Tutorials
concancon/Percolation
concancon/physProtoype_2d
concancon/ramp-modulo-comparison
concancon/simulations
a repository containing several module simulations