  This technical report proves components consistency for the Doubly Stochastic
Dirichlet Process with exponential convergence of posterior probability. We
also present the fundamental properties for DSDP as well as inference
algorithms. Simulation toy experiment and real-world experiment results for
single and multi-cluster also support the consistency proof. This report is
also a support document for the paper "Computationally Efficient Hyperspectral
Data Learning Based on the Doubly Stochastic Dirichlet Process".
