lemontree provides a very fast Java class for the Walsh Hadamard transform (WHT) and O'Connor transform (OCT). You can regard the OCT as a black box which turns arbitrary numerical data into data with a Gaussian distribution. There are inverse transforms, also. It has many applications, such as Random Projections, Compressive Sensing, Neural Nets, and Genetic algorithms.
libkdtree++ is a C++ template container implementation of k-dimensional space sorting, using a kd-tree. It sports a theoretically unlimited number of dimensions, and can store any data structure. Provided the data structure, it provides operator[0 - k-1] to access the individual dimensional components (arrays, std::vector already do) and a std::less implementation for the type of dimensional components. It has support for custom allocators, implements iterators, and provides standard find as well as range queries. It has amortised O(lg n) time (O(n lg n) worst case) on most operations (insert/erase/find optimised) and worst-case O(n) space, and also provides a means to rebalance and thus optimise the tree.
libphidgets is a user-space access library for the Phidget devices. It provides a generic and flexible way to access and interact with the Phidgets, and comes with all the advantages of a user-space library. It is based on libhid (which is based on libusb), thus it requires no HID support in the kernel. Furthermore, it aims to support all operating system supported by libusb/libhid: Linux, BSD, OS X, and Windows.
Evolvica is an evolutionary computation framework written in Java. The aim of the project is to provide a toolkit that enables developers to create genetic/evolutionary algorithms with minimal programming effort. The toolkit has a modular architecture and is highly extensible. It includes a visual algorithm editor, a source code editor, and a debugger.
PyWordNet is a Python interface to the WordNet database of word meanings and lexical relationships. It presents a concise interface to WordNet, that allows the user to type expressions such as N['dog'], hyponyms(N['dog'] ), and closure(ADJ['red'], SYNONYM) to query the database.