Embedding of feature space for pattern recognition using quantum computing

Tetsuo Hattori; Osamu Matoba; Bahram Javidi

doi:10.1117/12.477426

1 August 2002 Embedding of feature space for pattern recognition using quantum computing

Tetsuo Hattori, Osamu Matoba, Bahram Javidi

Proceedings Volume 4732, Photonic and Quantum Technologies for Aerospace Applications IV; (2002) https://doi.org/10.1117/12.477426
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

In order to deal with a general pattern recognition problem by quantum computing, this paper proposes an embedding method that corresponds a feature vector of n-dimensional space Vⁿ to a vector of the surface of Riemann sphere in the n+1 dimensional space Vⁿ⁺¹, keeping the topology among feature vectors. Because the radius of this Riemann sphere is one, the feature vectors are mapped into normalized vectors. This paper shows that multiple linear discriminant functions can be defined to separate two arbitrary clusters that are mapped onto the Riemann sphere in the space Vⁿ⁺¹. This paper also shows that we can define a unitary transformation that computes the signs of values of those multiple linear discriminant functions, in parallel by quantum computing.

Citation Download Citation

Tetsuo Hattori, Osamu Matoba, and Bahram Javidi "Embedding of feature space for pattern recognition using quantum computing", Proc. SPIE 4732, Photonic and Quantum Technologies for Aerospace Applications IV, (1 August 2002); https://doi.org/10.1117/12.477426

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