Max Pooling 1D Layer
Libraries:
Deep Learning Toolbox /
Deep Learning Layers /
Pooling Layers
Description
The Max Pooling 1D Layer block performs downsampling by dividing the input into 1-D pooling regions, then computing the maximum of each region.
The dimension that the layer pools over depends on the layer input:
For time series and vector sequence input in the
CT
format (two dimensions corresponding to channels and time steps, in that order), the layer pools over the time dimension.For 1-D image input in the
SC
format (two dimensions corresponding to spatial pixels and channels, in that order), the layer pools over the spatial dimension.
The exportNetworkToSimulink
function generates this block to represent a maxPooling1dLayer
object.
Limitations
The Layer parameter has limited support for the
'manual'
padding mode. It is recommended to use anmaxPooling1dLayer
object that has thePaddingMode
property set to'same'
.