
To reduce the size of the biosignal data is important because a huge amount of data is made by various experiments. In the paper, we efficiently compress the excitatory postsynaptic potentials (EPSPs) which is one of the biosignal types. To the best of authors' knowledge, EPSPs compression has not been studied yet. The EPSP signal has a feature that the adjacent signals in single excitatory postsynaptic potential have similar characteristics. Using this feature, we propose a method which removes temporal redundancy and statistical redundancy of EPSPs. The compressed and reconstructed EPSPs are similar to the original signal without the loss of analytic information.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
