A dependence-based framework using CDR and FMCA for time-series classification outperforms HMMs and spiking neural networks on the TI-46 speech corpus with a model under 5 MB.
The cross density ker- nel function: A novel framework to quantify statisti- cal dependence for random processes
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Time-Series Classification with Multivariate Statistical Dependence Features
A dependence-based framework using CDR and FMCA for time-series classification outperforms HMMs and spiking neural networks on the TI-46 speech corpus with a model under 5 MB.