Graduate Non-sinusoidal waveform model

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A ninth-grade student from Portugal is attempting to create a regression algorithm in Desmos to fit random binary inputs and predict future binary digits. They are seeking a model for generating non-sinusoidal waves, as their current approach based on Fourier's theorem is not yielding satisfactory results. Feedback suggests that their example is too linear and not representative of the desired output, with specific concerns about the parameters used. Additionally, there is skepticism about the feasibility of predicting future binary digits from random inputs. The discussion highlights the challenges of modeling non-sinusoidal waveforms effectively.
P3dr0
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Hi, I am a ninth-grade student from Portugal with nothing to do, and I have decided that I want to build a simple regression algorithm in Desmos (the online calculator) to fit random binary inputs and maybe predict the next binary digits (although that part may take a considerable amount of time). For now, I am just trying to find a way to create non-sinusoidal waves, but I can't find any model for it. Can anybody tell me a simple yet effective model for what I am trying to achieve?
PS: I have created an algorithm based on Fourier's theorem, but it doesn't work quite well. (I'll attach a photo and a link of what I have done.) This is the simplest version I have created so far, but I have tried other parameters. However, when I add more elements (more parameters), the function becomes noisier.

Link: https://www.desmos.com/calculator/h3nww18l8p
 

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What you have done is perfectly correct, but I am not sure that it is a good example of what you want to do. Notice that your example is perfectly linear with a slope of 1 and very near the (x=0, y=0) origin. The sin() function is also very linear with a slope of 1 near the origin. The tiny value of ##b## means that the inputs of sin() will be very close to 0 and the large value of ##a## means that the slope will be close to 1. If ##a=1/b##, the slope would be exactly 1 at the origin.
 
Welcome to PF.

P3dr0 said:
to fit random binary inputs and maybe predict the next binary digits
If the inputs are random, how can you do any predictions for future digits?
 
Here is a little puzzle from the book 100 Geometric Games by Pierre Berloquin. The side of a small square is one meter long and the side of a larger square one and a half meters long. One vertex of the large square is at the center of the small square. The side of the large square cuts two sides of the small square into one- third parts and two-thirds parts. What is the area where the squares overlap?

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