Preparing to experiment with RAM based Neural Networks

I got my hands on some old 30-pin RAM modules. One of the memory chips on each module appears to be arranged as 1024x1bit, meaning 10 address lines, 1bit of memory at each address. As far as I understand, this type of memory configuration is what is used for RAM based neural networks.

This article on teco.edu provides some insight into the concept of RAM based, logical neural networks: http://www.teco.edu/~albrecht/neuro/html/node23.html

At this point I'm still working on getting to where I can use the chips on a breadboard. Removing the ICs from the modules was not difficult, but preparing a piece of strip board to accept the ram chip was very time consuming.

After completing just one DIY adapter, I decided to just spend a few bucks and get some SOIC24 adapter kits from Ebay.

The actual IC pin arrangement is longer than SOIC24, even though the package only has 20 pins.

I had to bend the pins to match the solder pads and added a 100nF capacitor.

Now I just have a few more memory chips to solder and datasheets to study. Of course, before I get to actually design a simple, RAM based neural network, I have to first master interfacing with the chip, reading and writing data, refresh cycles etc. Fun stuff!