Abstract-Filters are time-invariant linear systems which are able to modify the characteristics of the signals connected to their input, so that only a specific portion of the frequency components in a signal can reach the output of the filter. In dynamic systems, digital filters are applied in order to improve system measurements with regards to performance and stability. The present article demonstrates a modification in a low pass filters having Hamming window within the sample space π. In this development, the sample space π is subdivided, wherein equation plots are added within a polynomial of order n. This technique provides the removal of unwanted frequency components in small angular frequency windows, providing the signal with acceleration towards the target when as compared to a low pass filter having Hamming window. In dynamic measurement systems, this feature is relevant, considering that the system shall have grater approximation to its target values, thus implementing an average which indicates the value being acquired in a more accurate and repetitive manner.

Abstract-The article shows a development methodology in the operation of finite impulse response (FIR) digital filters when built on computational methods based on general use processors.

This work developed a control algorithm for dynamical systems to high performance manner, in a way to produce an optimum output applying a modification in digital filters, capable of increasing the convergence zone within the desired cutoff frequency. Such task focused on consistently improving the challenge present in digital filters, which are time-invariant linear systems that are able to modify connected input signal characteristics, where only a specific signal component of the frequency is able to reach the filter output. In dynamic systems, digital filters are applied to optimize system measurements with respect to performance and stability. This work, through C and C# coding demonstrates a modification to windowed low-pass filters within the π sample space. The π sample space is divided, and small parts of the equation are added into a polynomial of degree n; this technique removes unwanted frequency components in small angular frequency windows, causing acceleration of the signal with respect to the windowed low-pass filter. This feature is very important in dynamic measurement systems because the system achieves an increased number in values closer to the target to obtain an average that indicates values with a high level of accuracy and repeatability. This work also conducted a series of experiments to verify and validate the control algorithm, this software was fully implemented in embedded industrial systems, which support lowlevel C coding language that is the industry standard.