Sequence and Series Reconstruction

In summary, the conversation discusses the concept of generating functions and their application in reconstructing missing information in a sequence. The question posed is whether it is possible to create a new generating function that can fill in the missing numbers in a sequence. The conversation also mentions the possibility of using this concept as a personal project for further exploration. The discussion ends with a question about the missing numbers in a sequence generated by a program.
  • #1
Liquid7800
76
0
After studying Generating Functions some, I wondered this question:

1). Take an arbitrary sequence of numbers for example:

{p1,p2,p3,p4...pN} and get/find a Generating Function for that sequence.

2). Now 'remove' an arbitrary sequence members from the above set :{p1,p2,p3,p4...p100} which might look like this after removal of arbitrary sequence members:

{p1,p2,,p8,,,,p20,p21,p22,,,,,,p45,,,...p100}

Now the question becomes:

Can you produce a Function (another Generating Function?) to make the sequence 'recognizable' again...how would you re-generate or re-facilitate the 'missing' sequence members or 'holes'...maybe using some combination of techniques to define a frame of 'reference' from an initial encoding from the original (full) sequence.

I have no idea if this problem(s) has been researched or even solved before...

but I was just thinking of how you could 'create' or 'fill' missing information mathematically...and the problem of sequence reconstruction came to mind.

If I am unclear as to what I am asking please let me know.

...I guess what I am looking for is some starting points, pre-requisite mathematical knowledge, theory, subject areas, refernce materials etc., from people who know what they are doing--- (anyone worked on this kind of thing before?)...

This is going to be a personal thing to mathematically immerse myself in as a project to explore, since I love series and Generating Functions.

Thanks for listening!
 
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  • #2
Isn't it that you can have a generating function for just every sequence? I mean I write out the series and the generating function is whatever comes you in the end.
In that case of your you cannot regenerate.

Here is a question back to you:
I wrote a program to generate random numbers 0-9. Then I deleted every other number. My result is "3751961764396515591391651592". Now what were the missing numbers in between?
 

Related to Sequence and Series Reconstruction

1. What is sequence and series reconstruction?

Sequence and series reconstruction is a statistical method used to estimate the values of missing or incomplete data points in a sequence or series. It involves using known data points to create a model or pattern, and then using that model to predict the missing values.

2. How does sequence and series reconstruction work?

The first step in sequence and series reconstruction is to identify the known data points and any missing or incomplete data. Then, a mathematical model is created based on the known data points. This model is then used to predict the missing values by filling in the gaps in the sequence or series.

3. What are the applications of sequence and series reconstruction?

Sequence and series reconstruction can be used in a variety of fields, including finance, economics, biology, and physics. It is commonly used to analyze and predict stock market trends, study genetic patterns, and understand natural phenomena such as weather patterns.

4. What are the limitations of sequence and series reconstruction?

Sequence and series reconstruction relies heavily on the accuracy of the initial data and the chosen mathematical model. If the data is incomplete or incorrect, the reconstructed sequence or series may not be accurate. It also assumes that the underlying pattern or model remains consistent throughout the entire sequence or series.

5. How can sequence and series reconstruction be validated?

To validate the accuracy of a reconstructed sequence or series, it is important to compare the predicted values to actual data points, if available. Additionally, cross-validation techniques, such as splitting the data into training and testing sets, can be used to assess the performance of the reconstruction method. It is also important to consider the complexity of the chosen model and ensure it is not overfitting the data.

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