<p>Overview and Introduction.- PART I: Fundamentals.- Simplex Volume Calculation.- Discrete Time Kalman Filtering in Hyperspectral Data Prcoessing.- Target-Specified Virtual Dimesnionality.- PART II: Sample Spectral Statistics-Based Recursive Hyperspectral Sample Prcoessing.- Real Time Recursive Hyperspectral Sample Processing of Constrained Energy Minimization.- Real Time Recursive Hyperspectral Sample Processing of Anomaly Detection.- PART III: Signature Spectral Statistics-Based Recursive Hyperspectral Sample Prcoessing.- Recursive Hyperspectral Sample Processing of Automatic Target Generation Process.- Recursive Hyperspectral Sample Processing of Orthogonal Subspace Projection.- Recursive Hyperspectral Sample Processing of Linear Spectral Mixture Analysis.- Recursive Hyperspectral Sample Processing of Maximimal Likelihood Estimation.- Recursive Hyperspectral Sample Processing of Orthogonal Projection-Based Simplex Growing Algorithm.- Recursive Hyperspectral Sample Processing of Geometric Simplex Growing Simplex Algorithm.- PART IV: Sample Spectral Statistics-Based Recursive Hyperspectral Band Prcoessing.- Recursive Hyperspectral Band Processing of Constrained Energy Minimization.- Recursive Hyperspectral Band Processing of Anomly Detection.- Signature Spectral Statistics-Based Recursive Hyperspectral Band Prcoessing.- Recursive Hyperspectral Band Processing of Automatic Target Generation Process.- Recursive Hyperspectral Band Processing of Orthogonal Subspce Projection.- Recursive Hyperspectral Band Processing of Linear Spectral Mixture Analysis.- Recursive Hyperspectral Band Processing of Growing Simplex Volume Analysis.- Recursive Hyperspectral Band Processing of Iterative Pixel Puirty Index.- Recursive Hyperspectral Band Processing of Fast Iterative Pixel Purity Index.- Conclusions.- Glossary.- Appendix A.- References.- Index.</p>