1. Introduction and Preliminaries
Sequence spaces have been fundamental to the development of functional analysis from its early stages. Among the most significant spaces are 
, and 
 which emerged as important specific cases of Banach spaces. These sequence spaces are widely utilized across various areas within functional analysis, including the theory of functions, locally convex spaces, summability invariance, and matrix transformations. Their significance in these areas is well-documented in the literature (see [
1,
2,
3,
4,
5] and references therein), highlighting their crucial role in advancing both theoretical and applied aspects of the field.
In numerous investigations, including the work of Mursaleen et al. [
6], sequence spaces defined by Orlicz functions have been a primary focus. The concept of 
-convergence, introduced by Kostyrko et al. [
7], extends statistical convergence by utilizing an ideal on the set of natural numbers to establish this generalization. Subsequent studies, such as those by [
8,
9], have explored sequence spaces using the notion of 
-convergence. Additionally, Kuratowski [
10] introduced the concept of an ideal on a nonempty set, which has further contributed to the development and understanding of these mathematical structures. Sequence spaces can be further generalized through the introduction of paranorms, as seen in paranormed sequence spaces, which extend traditional norm concepts by relaxing certain norm properties. Additionally, the incorporation of various convergence criteria, such as 
-convergence and Musielak–Orlicz functions, provides new insights into sequence behavior and broadens the scope of analysis. These extensions allow for the exploration of more complex relationships and properties within sequence spaces.
Definition 1. A paranormed space is a vector space  equipped with a function  called a paranorm, which satisfies the following conditions:
- 1. 
-  for all ; 
- 2. 
-  if and only if ; 
- 3. 
-  for all ; 
- 4. 
-  for all . 
 An ideal  is defined as a nonempty set of subsets of X that has the following properties:
- (i)
- If  and  then ; 
- (ii)
- If  and  then . 
We define  as non-trivial if it does not equal the empty set and . Additionally,  is considered admissible if it satisfies the condition of being non-trivial and  for each  A non-trivial ideal  is maximal if there does not exist any nontrivial ideal  such that .
Definition 2. A sequence  is said to be -convergent to a number L if for every , . In this case we write 
 The concept of difference sequence spaces was first introduced by Kızmaz [
11], who studied the space 
, where 
 represents the spaces 
, and 
, 
 for all 
 and 
 denotes the space of all real or complex sequences. This concept was later expanded by Tripathy et al. [
12], who introduced generalized difference operators. For non-negative integers 
n and 
m, they defined the sequence spaces 
, for 
 where 
 and 
 for each 
. The difference operator 
 can be expressed using the binomial formula as in [
13] by
      
Further, in the context of paranormed spaces and Musielak–Orlicz function spaces, 
-convergence has been studied to explore new sequence spaces that offer more refined properties. Khan and Tuba [
14] explored the application of ideal convergence within the context of paranormed sequence spaces, specifically those defined by the Jordan totient function. Their work contributes to the growing body of research that investigates the interplay between ideal convergence and functional spaces, expanding its applicability to new mathematical structures and providing deeper insights into the nature of convergence under different norms. The study of 
-convergence has also been enriched by examining its interaction with other sequence space constructions, such as those defined by Musielak–Orlicz functions and modulus functions. These developments have opened new avenues for research in both theoretical and applied mathematics. Mursaleen [
15] introduced several sequence spaces by employing the concepts of ideal convergence and Musielak–Orlicz functions. The concept of 
-convergence has been significantly generalized and extended in various directions in recent years. For instance, Tripathy et al. [
16] investigate generalized difference ideal convergence within the framework of generalized probabilistic 
n-normed spaces. Their study aims to bridge the gap between ideal convergence and probabilistic normed spaces, providing new insights into how sequences converge under different probabilistic norms.
Malik and Das [
17] expanded on this concept by investigating the 
-convergence of sequences of subspaces in inner product spaces, a crucial area in functional analysis with implications for various applications, including quantum mechanics and signal processing. Their work offers a fresh perspective on the behavior of subspaces under ideal convergence, exploring how this generalized notion can capture convergence phenomena that are not observable through classical methods. For further details on ideal convergence, please refer to references ([
18,
19,
20,
21]) and references therein.
Tang and Xiong’s [
22] study investigates how sequences in quasi-metric spaces can be analyzed through the lens of 
-convergence, focusing on the conditions under which a sequence is 
-convergent. They explore the implications of 
-convergence for the structure of quasi-metric spaces, providing new theoretical results and extending the application of 
-convergence to these more general spaces. These studies underscore the rich interplay between 
-convergence and paranormed spaces, expanding the theoretical framework and offering new insights into their practical applications. For more information about the ideal convergent sequence, we refer to ([
23,
24,
25,
26,
27,
28,
29,
30,
31,
32]) and references therein. In recent developments, various authors have extended the classical difference sequence spaces by incorporating more generalized difference operators and examining their interaction with various functional constructs such as Musielak–Orlicz functions and ideal convergence. These advancements have led to the creation of new sequence spaces that offer greater flexibility and applicability in both theoretical and practical settings. For more information about these, see ([
33,
34,
35,
36]) and references therein.
Suppose that 
X is a linear space. A function 
 is known to be convex, if the following inequality holds:
      for all 
, and 
.
A sequence space X is solid (or normal) if  whenever  for all sequences  of scalars with  for all .
Theorem 1 ([
13,
37])
. Let f be a convex function with . Then  for all . An Orlicz function is a function 
 which is continuous, non-decreasing, and convex, with 
, and 
, as 
 An Orlicz function 
M is said to satisfy the 
-condition, if for each 
 there exists a constant 
 such that 
 Musielak–Orlicz functions are known to be sequence 
 of Orlicz functions ([
38,
39]). A sequence 
 is defined by
      
      which is called the complementary function of a Musielak–Orlicz function 
; the Musielak–Orlicz sequence space 
 and its subspace 
 are defined as follows,
      
      where 
w is the space of all real or complex sequences and 
 is a convex modular defined by
      
Theorem 2 ([
13,
37])
. An Orlicz function M satisfies the -condition if and only if for each  and each  there exists a constant  such that Notice that the function  where  and , is an Orlicz function that satisfies the -condition, as 
Recent advancements have expanded this field by incorporating Musielak–Orlicz functions and ideal convergence. Musielak–Orlicz functions, which generalize the classical Orlicz functions, allow for a broader and more flexible approach to defining and studying sequence spaces. These functions enable the construction of sequence spaces that accommodate a wide range of growth conditions and convergence criteria. The primary objective of this paper is to present the concept of -convergence for sequences along with an investigation of Musielak–Orlicz functions of order .
The sequence spaces we are defining play a crucial role in extending the theory of sequence spaces by incorporating -convergence and Musielak–Orlicz functions. These spaces are significant in several areas, including summability theory, where they refine the analysis of series convergence; functional analysis, by providing new frameworks for understanding operator behavior; and approximation theory, where they enhance methods for approximating functions. Their importance extends to practical applications such as mathematical modeling and numerical methods, where they offer sophisticated tools for handling various convergence criteria and sequence behaviors.
The spaces , , and  are essential in various mathematical and applied fields. They are utilized in approximation theory to assess function convergence and approximation properties. In functional analysis, they help in understanding the behavior of linear operators and functionals, particularly in generalized settings where traditional norms might be too restrictive, and in the theory of differential equations to analyze solution properties and stability. Additionally, these spaces find applications in control theory for system design and signal processing for analyzing signal behavior and transformations. Their ability to handle different types of convergence and function spaces makes them valuable tools in both theoretical and practical contexts.
  3. Main Results
Let 
 be a Musielak–Orlicz function and 
 be a bounded sequence and 
 For each 
 Then we define the following sequence spaces as the following:
      and
      
In this section, we study some topological and algebraic properties of the above defined sequence spaces.
Firstly, we construct some examples related these spaces:
Example 1. Consider the sequence  defined by  for  and  Let  be a Musielak–Orlicz function and . Then the sequence ξ belongs to the space  ifThis condition is satisfied if , i.e., for sufficiently large p. Thus,   Example 2. Consider the sequence  for  and  Let  be a Musielak–Orlicz function and . If , then  because  Example 3. Let  for  with Musielak–Orlicz function  and . For , the sequence  is bounded and belongs to the space  because  Example 4. Take  and Musielak–Orlicz function  with . The sequence  if  Theorem 3. If  be a Musielak–Orlicz function, then  and  are linear spaces over the field of complex number .
 Proof.  Suppose that , and .
For 
 to be given, we have to show that there exist 
 and 
 such that
        
Since 
, there exist two numbers 
 and 
 such that
        
        and
        
        where 
 and 
Assume that  and  Then, by using the triangular inequality and also the fact  is non-decreasing, we have
		
Since 
 is convex. Thus, we have
		
Let 
 Then,
		
If 
, then from last inequality, we have
		
        this implies 
. Thus, if 
 and 
, it follows that 
. Therefore, 
 and hence, 
 is a linear space. Similarly, we establish that 
 is a linear space.    □
 Theorem 4. If  is a Musielak–Orlicz function, then  is a linear space over the field of complex number .
 Proof.  Suppose that 
, and 
 We have to show that there exist two positive numbers 
Q and 
 such that
        
By hypothesis, there exist four positive numbers 
, and 
 such that
        
        and
        
        where 
 and 
.
Suppose that  and  Thus, we have
		
Let 
 Then,
		
If 
 then from last inequality, we have
		
        this implies that 
. Thus, if 
 and hence, 
, it follows that 
 Therefore 
. Hence, 
 is a linear space over the field of complex number 
.    □
 Corollary 1. If  be a Musielak–Orlicz function, then  and  are linear spaces over the field of complex number .
 Theorem 5. The spaces  and  are paranormed spaces with paranorm defined bywhere    Proof.  It is clear that  Since  we get . Let us take  and  in .
Let 
Let 
 and 
. If 
, then we have
		
Thus 
 and
        
Suppose that 
 where 
, and 
 as 
.
We have to show that  as .
Let 
		If 
 and 
, then we observe that
        
From the above inequality, it follows that
        
        and consequently,
        
This completes the proof.    □
 Theorem 6. Let  and  be two Musielak–Orlicz functions which satisfies the -condition. The following statement holds:
- 1. 
- If  be a bounded sequence with  then  for  
- 2. 
-  for  
 Proof.  (1) Let 
. There exists 
 such that
        
Given 
. Since each 
 is continuous at 0 from right, there exists 
 such that 
 implies that 
 Suppose that 
 for each 
. Defining the sets 
 and 
 Observe that
        
If 
 then 
 By Theorem 
, we have 
 and so,
        
For 
 we have 
 Since each 
 satisfies the 
-condition and non-decreasing for each 
, by Theorem 
, there exists a constant 
 such that
        
Thus,
        
Therefore, from the above result, it follows that
        
Since 
 we have
        
Therefore,  and hence 
(2) Let 
 There exist two numbers 
 and 
 such that
        
        and
        
Let 
 and 
. By applying Maddox’s inequality, we get
        
Therefore, from the above inequality, we get
        
Hence, 
 Therefore,
        
Theorem 6 is proved.    □
 Theorem 7. If  then the following inclusion holds:
- 1. 
- , 
- 2. 
- , 
- 3. 
- , 
- 4. 
- , 
- 5. 
- . 
 Proof.  We have to prove 
 only. The proof of remaining parts directly follows from 
. Assume that 
. For 
 to be given, we have to show that there exists 
 and 
 such that
        
Since 
, there exists 
 and 
 such that
        
        where 
 and 
 Suppose 
 and 
. Since 
 is non-decreasing and convex for each 
. Put 
, we have
        
Let 
 Then,
        
If 
 then from above inequality, we have
        
        this implies that 
. Therefore, 
 and hence 
. Therefore, 
 and so 
.    □
 Theorem 8. The sequence spaces  and  are solid and hence monotone.
 Proof.  Let 
 and let 
 be a sequence of scalars with 
 for each 
. There exist two positive numbers 
 and 
Q such that
        
Let
        
If 
, then
        
        which implies that 
. Thus, 
 and hence, 
 This shows that 
 for all sequence of scalars 
 with 
 for each 
, whenever 
. Therefore, 
 is solid. Similarly, we provided a proof for 
.    □