Everyone is how to handle the sensor data?
Mathematical modeling how to understand?

CodePudding user response:

Mathematical modeling, which is based on the actual problem to establish the mathematical model, the mathematical model for solving, and then according to the results to solve practical problems,

CodePudding user response:

More simple and direct is PID algorithm, is suitable for most, but the test is a bit of trouble, can I speak to PID related information

CodePudding user response:

refer to the second floor @ contradict response:

simple direct is PID algorithm, suitable for the most part, but the test is a bit of trouble, you can find the PID related information

This is mainly used in the control aspect,

CodePudding user response:

reference dancingmoon08 reply: 3/f

Quote: refer to the second floor of the @ contradict reply:

simple direct is PID algorithm, is suitable for most, but the test is a bit of trouble, can I speak to PID related information

This is mainly used in the control aspect,

to deal with the situation

CodePudding user response:

Simple photosensitive sensor, for example, for a certain number of times, and then the filter, and then adjust the brightness and so on

CodePudding user response:

reference 5 floor @ contradict reply:

simple photosensitive sensor, for example, for a certain number of times, and then filter, and then to adjust brightness, such as

Well, yes, curve fitting with what

CodePudding user response:

Regression analysis involves two variables, only said a yuan regression analysis, the main task of a yuan return from a variable in the two related variables to estimate another variable, be estimated variables, called the dependent variable, can be set to Y; Estimate variables, according to the independent variable, is set to X, regression analysis is to find A mathematical model for Y=f (X), makes the estimates from X Y can be used to compute A function type, when Y=f (X) is in the form of A linear equation, is called A yuan linear regression, this equation can generally be said for Y=A + BX, based on the least square method or other methods, the constant term can be identified from the sample data with the regression coefficient B value, A, B is determined, there is A X observed value, can get A Y estimates, the regression equation is reliable, how big is the estimate of the error, should also through significance test and error calculation, have significant correlation, and sample size, etc., are the factors affecting the reliability of the regression equation,