Flexibly programmable opto-electronic analogic CNN computer (POAC) implementation applying an efficient, unconvential optical correlator architecture
To overcome shortcomings of the currently available optical computer architectures a programmable opto-electronic CNN array computer (POAC) is introduced. It combines the optical correlators' supreme resolution and complexity with the versatility of the single chip adaptive visual CNN-UM sensor and processor arrays. The system is grounded on an unconventional optical correlator architecture, which is a modified joint Fourier transform correlator. This architecture uses the angular coding of the template pixels and applies the template not in the recording phase, but in the reconstruction phase of correlation. Feasibility of this concept has been successfully demonstrated by a breadboard model. It computes correlation in two consecutive steps: First a hologram of the input image is recorded in a dynamic holographic material (we used chemically-modified Bacteriorhodopsin film samples). Next, angularly-coded read-out beams reconstruct the appropriately weighted and shifted replicas of the stored input image. Superposition of these copies produces the correlogram. A programmable adaptive sensor array, a special Visual CNN-UM chip detects the resulting correlogram. So, both the sensing and the required post-processing steps are accomplished in a parallel way. The introduced opto-electronic architecture provides exceptional synergy and good compromise of the applicable technologies and the system performance.
optical correlator optical computer cnn (cellular neural network) target recognition jtc (joint transform correlator) optical cnn