  Dimensionality reduction represents the process of generating a low
dimensional representation of high dimensional data. Motivated by the formation
control of mobile agents, we propose a nonlinear dynamical system for
dimensionality reduction. The system consists of two parts; the control of
neighbor points, addressing local structures, and the control of remote points,
accounting for global structures. We also include a brief mathematical
observation of the model and its numerical procedure. Numerical experiments are
performed on both synthetic and real datasets and comparisons with existing
models demonstrate the soundness and effectiveness of the proposed model.
