Sparse coding provides a class of algorithms for finding succinct representations of stimuli; given only unlabeled input data, it discovers basis functions that capture higher-level features in the ...

Modifying an simpler attempt with a better algorithm The only difference here from what we did before is the last sentence, where we add a set of constraints on the dictionary atoms. Solving the ...

Accurately modelling the nonlinear dynamics of a system from measurement data is a challenging yet vital topic. The sparse identification of nonlinear dynamics (SINDy) algorithm is one approach to ...

Numenta compared sparse and dense networks by running its algorithms on Xilinx FPGAs (Field Programmable Gate Array) for a speech recognition task using the Google Speech Commands (GSC) dataset.

The alternative, sparse coding, tends to be used for memory recall and sensory representations. Here, a single neuron only conveys a limited amount of information (i.e., there's something moving ...