Abstract: The creped multi-ply tissue products are durable, smooth and have low levels of Slough. In certain instances, the creped multi-ply tissue products are produced using a creping composition comprising a non-crosslinked latex polymer. The creped multi-ply tissue products may have a geometric mean tensile (GMT) from about 700 to about 1,500 g/3?, a basis weight from about 45 to about 60 gsm and a Slough less than about 2.00 mg, such as from about 0.10 to about 2.00 mg. The inventive tissue products also have good durability, such as a Durability Index from about 10.0 to about 20.0, smooth surfaces, such as a TS750 value from about 15.0 to 40.0 and low stiffness, such as a Stiffness Index less than about 10.0.

Abstract: A nonlinear neuron classifier comprising a neuron array including a plurality of neuron chips each including a plurality of neurons of variable length and variable depth, the chips processing input vectors of variable length and variable depth that are input into the classifier for comparison against vectors stored in the classifier, wherein an NSP flag is set for a plurality of the neurons to indicate that only that plurality of neurons is to participate in the vector calculations. A virtual content addressable memory flag is set for certain of the neuron chips to enable functions including fast readout of data from the chips. Results of vector calculations are aggregated for fast readout for a host computer interfacing with the classifier.

Abstract: A nonlinear neuron classifier comprising a neuron array including a plurality of neuron chips each including a plurality of neurons of variable length and variable depth, the chips processing input vectors of variable length and variable depth that are input into the classifier for comparison against vectors stored in the classifier, wherein an NSP flag is set for a plurality of the neurons to indicate that only that plurality of neurons is to participate in the vector calculations. A virtual content addressable memory flag is set for certain of the neuron chips to enable functions including fast readout of data from the chips. Results of vector calculations are aggregated for fast readout for a host computer interfacing with the classifier.