Abstract:

In order to give the algorithm's ability to distinguish general parameters, this paper proposes the concept of algorithm parameter resolution. This paper combines the idea of clustering to give the definition and calculation method of parameter resolution. The least squares estimation and the total least absolute deviations estimation method are used to analyze the parameter resolution of unary linear regression model. Experimental results show that both algorithms have properties:as the SNR increases, the accuracy of the parameter resolution is higher; the local parameter resolution is consistent with the overall parameter resolution; the standard deviation of noise and parameter resolution of least squares satisfy a linear relationship which has been proved by using interval estimation theory. Finally, the least squares and the total least absolute deviations are used to estimate the parameter resolution of two similar audio signals. The experimental results illustrate the rationality and effectiveness of the definition of parameter resolution. Parameter resolution is a criterion for measuring whether two similar signals can be separated, it is also an effective indicator for evaluating the accuracy of models and algorithms.

Key words: Parameter Resolution, Least Squares, Total Least Absolute Deviations, Clustering, Interval Estimation