Estimating parameters of static objects with matrix input and output

The least-squares method is widely applied when processing results received at the solution of tasks which are connected, for example, with the identification of dynamic objects or with the pattern recognition. The article considers the application of recurrent least-squares method for the parameters determination of a static object with a matrix input and a matrix output. As test input signals it is offered to use signals like a meander with single amplitude. The estimation results of the object parameters are given for a case when Gaussian noises occur at the object output. The simulation of input signals which are realizing impact on an object, and the iterative procedure of the least-squares method are executed in the Simulink environment. The blocks which are realizing the formation of the iterative procedure of parameters estimation correspond to basic formulas which are a part of the algorithm of the recurrent least-squares method. On the example of the second order object the estimates received as a result of the recurrent estimation constructed scheme are given in the graphic form. It is possible to mark that the fast convergence of the parameters estimates to basic parameter values of an object is stated. The behavior diagram of the gain coefficient which is present at the algorithm of the recurrent least-squares method is demonstrated. Testing the algorithm of the object parameters estimation was carried out using input signals like a meander with different periods. The simulation results show that the algorithm gives the good estimates of unknown parameters even in the presence of the considerable noise watched on the object output. The offered approach is supposed to be used for the parameters estimation of the higher order objects with the different parameters quantity.