Quantized‐output‐based least squares of ARX systems

This paper considers the estimates of parameters stochastic autoregressive exogenous input (ARX) systems with quantized data. The error caused by data brings difficulties to parameter estimation ARX systems. Therefore, I start boundedness and design size thanks good properties least squares. Then influences noise system itself bounded on are analyzed, respectively. inputs designed make satisfy persistent excitation condition, so as ensure error. A numerical example is given demonstrate theorem.