Neural based orthogonal data fitting : the EXIN neural networks Written by three leaders in the field of neural based algorithms Neural Based Orthogonal Data Fitting proposes several neural networks all endowed with a complete theory which not only explains their behavior but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view including: as a differential geometry problem as a dynamic problem as a stochastic problem and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Where most books on the subject are dedicated to PCA (principal component analysis) and consider MCA (minor component analysis) as simply a consequence this is the fist book to start from the MCA problem and arrive at important conclusions about the PCA problem.