Quite a number of vision and cognitive scientists have urged me to send out a notification of my recently published book on illusions, which contains many new effects, as well as the traditional classic ones. It is the best published collection so far. Although the book is in a popular format, the over 160 full page illustrations are of high quality and in color, which makes it worthwhile collection for anyone studying vision and cognitive science. If you have discovered some new effects, I would be most interested in hearing about them, as I am preparing an authoritative treatise for MIT Press. Dear Connectionists, I am pleased to announce the availability of my Ph.D. thesis for download in electronic format.
Comments are welcome.
That eases system users' burdens to a great extent. It is essential in efficient and accurate learning for supervised learning systems such as neural networks to be able to utilize knowledge in the forms of such as logical expressions, probability distributions, and constraint on differential data along with provided desirable input and output pairs. Neural networks, which can learn constraint on differential data, have already been applied to pattern recognition and differential equations. Other applications such as robotics have been suggested as applications of neural networks learning differential data. In this dissertation, we investigate the extended framework introduce constraints on differential data into neural networks' learning.