We introduce a novel neural network with a trigonometric interconnection called the T-Model neural network in this paper. A VLSI implementation of the T-Model neural network based on CMOS current-mode circuits is also presented. The circuit is completely compatible with standard VLSI technology. A set of neuron-type elements of CMOS current-mode circuits is described and a very large scale neural network is also synthesized. The feasibility and the operation principle of the synthesis of the T-Model neural network using CMOS current-mode circuits are demonstrated and confirmed by experimental results of fabricated CMOS VLSI neural chips.

The mappings from multidimension to one-dimension, or the inverse mappings, are theoretically discussed as space-filling curves, i.e., Peano curves. The Peano scan is an application of a Peano curve to the scanning of images, and it is used for analyzing, clustering, or compressing an image, and for limiting the number of the colors used in an image. The horizontal and vertical sizes of the scanned array, however, must be a power of two. To avoid such a case, we generalize the Peano scan for scanning an arbitrarily-sized array, whose horizontal and vertical sizes are possible to be different. First we propose a binary scan which is made of binarily recursive divisions of an image. As the Peano scan is characterized by the statistical property of Brownian motion, further we describe that binary scan can be also optimized to have such statistical property.

This letter describes a high-speed wide dynamic range optical pulse receiver for multichannel biotelemetry system. A non-linear feedback impedance approach in transimpedance type receiver has been proposed for achieving wide dynamic range characteristics. A prototype receiver integrated circuit (IC) has been designed and implemented by bipolar IC process.