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1. Introduction
For any
The discovery of q-numbers by Jackson has been applied to various fields of mathematics such as
Definition 1.
The Gaussian binomial coefficients are defined by
Theorem 1.
Let
Definition 2.
Let
Definition 3.
The definition of the
We can prove that
Definition 4.
We define the
If this function,
In a deep learning network, we pass the nonlinear function through the nonlinear function, rather than passing it directly to the next layer. The function used at this time is called the activation function. Among these activation functions, there is a sigmoid function. The definition of sigmoid function is as follows.
Definition 5.
Let
In order to find various applications, various studies were done by investigating the sigmoid function. For example, a variant sigmoid function with three parameters has been employed in order to explain hybrid sigmoidal networks, and sigmoid function, which is also called logistic function, has been defined using flexible sigmoidal mixed models based on logistic family curves for medical applications (see [15–19,23]). The following theorem has several basic properties for sigmoid polynomials.
Theorem 2.
Let
In this paper, in order to confirm the relationship between the sigmoid polynomial including q-numbers and other polynomials, let us check the following famous polynomials including q-numbers.
The Bernoulli, Euler, and Genocchi polynomials have been widely studied in various mathematical applications including number theory, finite difference calculus, combinatorial analysis, and p-adic analytic number theory. These numbers and polynomials are very well known and most mathematicians are familiar with them because of their importance (see [1,11,13,20,22,24,25]).
Definition 6.
Finding the properties of sigmoid polynomials combined with q-numbers in various ways is the main topic of this paper. In Section 2, we look for the basic properties of
2. Some Basic Properties of Sigmoid Polynomials Combining
In this section, we first define the number of sigmoid and polynomials that combine the
Definition 7.
Let
From Definition 7, we have
We note that
Theorem 3.
For
Proof.
From Definition 7, we can find a relation between
Comparing the both sides of
Corollary 1.
From Theorem 3, the following holds:
Theorem 4.
Let
Proof.
Considering
Using
Corollary 2.
From Theorem 4, one obtains
Theorem 5.
Let
Proof.
(i) For
And we note that
Using Cauchy’s product, we obtain
(ii) We omit a proof of (ii) due to its similarity to (i).
Theorem 6.
Let
Proof.
We can consider that
From the form A, we can find
The required relation follows on comparing the coefficients of
Corollary 3.
Let
Theorem 7.
For
Proof.
(i) We suppose that
From the form B, we can obtain
Therefore, we find result of Theorem 7 (i), (ii), and (iii). To find results of (ii) and (iii), we consider
We omit the proof of (ii) and (iii) because we can derive required results in the same method as (i).
Theorem 8.
Let
Proof.
(i) Using
Applying Corollary 1 (ii) again in the equation above, we complete a proof of (i).
(ii) We omit the proof of (ii) because we can derive required results in the same method as (i) and use Theorem 3.
Theorem 9.
For
Proof.
(i) Transforming the generating function of
We can note a property of
Hence, we can find the required result.
(ii) We omit a proof of (ii) due to its similarity to (i).
Theorem 10.
Let
Proof.
(i) Using
Comparing with Theorem 8 and result of the equation above, we can find the required result.
(ii) We omit a proof of (ii) due to its similarity to (i).
Theorem 11.
Let
Proof.
We recall the definition of
Applying
Hence, we finish a proof of Theorem 10.
Corollary 4.
From Theorem 11, one holds
3. The Observation of Scattering Zeros of the
In this section, we try to find approximate roots of sigmoid polynomials combined with
First, some q-sigmoid polynomials can be confirmed as follows:
Furthermore, here are several
Based on this polynomial, through the program we try to examine the location of the polynomial roots when the
Figure 2 shows the result when
Table 1 shows the actually calculated approximate values for
Table 1
Approximate zeros of
−1, −0.620721–0.0361286 i, −0.620721 + 0.0361286 i | |
−0.60958–0.108614 i, −0.60958 + 0.108614 i, −0.588669–0.180732 i | |
−0.588669 + 0.180732 i, −0.558909–0.250923 i, −0.558909 + 0.250923 i | |
−0.520715–0.31767 i, −0.520715 + 0.31767 i, −0.474449–0.379636 i | |
−0.474449 + 0.379636 i, −0.420612–0.435565 i, −0.420612 + 0.435565 i | |
−0.359937–0.484249 i, −0.359937 + 0.484249 i, −0.222503–0.555698 i | |
−0.222503 + 0.555698 i, −0.148551–0.577093 i −0.148551 + 0.577093 i | |
−0.0730754–0.588612 i, −0.0730754 + 0.588612 i, −0.0137537 | |
0.00256565–0.590362 i, 0.00256565 + 0.590362 i, 0.0771461–0.58261 i | |
0.0771461 + 0.58261 i, 0.14955–0.565738 i, 0.14955 + 0.565738 i | |
0.218754–0.540216 i, 0.218754 + 0.540216 i, 0.283816–0.506599 i | |
0.283816 + 0.506599 i, 0.343876–0.46552 i, 0.343876 + 0.46552 i | |
0.398157–0.417686 i, 0.398157 + 0.417686 i, 0.445974–0.363867 i | |
0.445974 + 0.363867 i, 0.486731–0.304893 i, 0.486731 + 0.304893 i | |
0.519934–0.241641 i, 0.519934 + 0.241641 i, 0.545183–0.175026 i | |
0.545183 + 0.175026 i, 0.562181–0.105989 i, 0.562181 + 0.105989 i | |
0.570729–0.0354924 i, 0.570729 + 0.0354924 i |
In Figure 3, when
Figure 3 at
Based on these results, we can confirm the accumulation structure of root in 3 dimensions as shown in Figure 4. It can be confirmed that the structure of root is different according to the change of
Conjecture 1.
(1)
When q is close to 0 and
(2)
When q = 50 with
(3)
When
4. Conclusion
In this paper, approximate roots are obtained by programming based on the theorems in Section 2. By looking for the guesses in Section 3, we were able to visually confirm the properties of the
Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (no. 2017R1E1A1A03070483).
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Abstract
The sigmoid polynomials combining
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