Burcu Erkmen

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Natural organs are spatially heterogeneous, both in material composition and in the cell types within. Engineered tissues, in contrast, remain challenging to create, especially if the goal is to spatially position multiple cell types in a heterogeneous pattern in three dimensions (3D). Here, we describe a simple, inexpensive , yet extremely precise method(More)
—This work presents efficient constrained optimization methods for sizing of a differential amplifier with current mirror load. The aim is to minimize MOS transistor area using three evolutionary algorithms, differential evolution, artificial bee colony algorithm and harmony search. Simulation results demonstrate that proposed methods not only meets design(More)
In this brief, conic section function neural network (CSFNN) circuitry was designed for offline signature recognition. CSFNN is a unified framework for multilayer perceptron (MLP) and radial basis function (RBF) networks to make simultaneous use of advantages of both. The CSFNN circuitry architecture was developed using a mixed mode circuit implementation.(More)
In this paper, a circuit system of General Purposed Conic Section Function Neural Network is presented. The feed-forward analog computational cells have been designed by using the current mode approach. The network is trained in a chip-in-the-loop fashion with a host computer implementing the training algorithm. The network inputs and the feed-forward(More)