'Network weights' presentation slideshows

Protein Structure Prediction

649 views • 29 slides

Engineered and Artificial Systems

Engineered and Artificial Systems. Engineered and Artificial Systems. Methodological and applied research Modelling of learning and perception Bayesian Object Recognition (Jouko Lampinen) Computational Neuroscience via Autonomous Robotics (Harri Valpola) Engineered nanosystems

419 views • 22 slides

Decision making in episodic environments

255 views • 17 slides

Similarity Measures for Rhythmic Sequences

251 views • 15 slides

The Freeman Model as an Associative Memory: Application to Static Pattern Recognition

The Freeman Model as an Associative Memory: Application to Static Pattern Recognition. Mark D. Skowronski, John G. Harris, and Jose C. Principe Computational NeuroEngineering Lab Electrical and Computer Engineering University of Florida, Gainesville, FL April 25, 2004. Introduction.

256 views • 9 slides

Introduction

Half-Lives for R-Process Nucleosynthesis Using the ANN Statistical Global Model. targ et ( Log 10 T ? - , exp ). Neural Network. input [Z,N, ?]. p 1. Output ( Log 10 T ? - , calc ). comparison. a. weights adjustment.

114 views • 1 slides