D. N. Nissani

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A novel quasi-MLD solution denoted Directional Lattice Descent (DLD in short) is proposed in this paper to the MIMO and ISI detection problems, which exhibits quadratic time complexity. We formulate the detection problem as that of finding the closest point in a lattice. This is solved by a proposed discrete space analogy to the continuous-space gradient(More)
This paper introduces a novel Neural Network model intended for classification of patterns into distinct categories. Arbitrary accurate category formation in a predefined feature space is asymptotically achieved by means of an unsupervised learning algorithm. Learning takes place by assignment of labeled neurons to unrecognized input exemplars and(More)
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