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In this paper, we show how a cellular nonlinear network with 1-bit weight programmability can be used for processing black and white image data. When using such a binary-programmable network, some templates need to be processed algorithmically, in other words, divided into subtasks that are processed consecutively. We classify templates into groups based on(More)
We present methods for processing the LBPs (local binary patterns) with a massively parallel hardware, especially with CNN-UM (cellular nonlinear network-universal machine). In particular, we present a framework for implementing a massively parallel face recognition system, including a dedicated highly accurate algorithm suitable for various types of(More)
Analog to digital converters are used in extremely many applications to convert real world signals into digital words. The converter presented in this paper, is designed for a Cellular Nonlinear Network type system, where A/D converters are included in each cell to transform the gray scale value to be stored in a 6 bit SRAM memory bank. Because of this, the(More)
Both respiratory and cardiac motions reduce the quality and consistency of medical imaging specifically in nuclear medicine imaging. Motion artifacts can be eliminated by gating the image acquisition based on the respiratory phase and cardiac contractions throughout the medical imaging procedure. Electrocardiography (ECG), 3-axis accelerometer, and(More)