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-Program allows you to display a GENEO generated through the selection of a
-group, a permutant of the group and an image as input data function.The result
-is then normalized through a constant that can be changed by the user. The
-software obtains the result shown through the application of theorems and
-mathematical settings described by the paper
-
-"On the Construction of Group Equivariant Non-Expansive Operators via
-Permutants and Symmetric Functions"
+## Introduction
+
+Welcome to the repository of GDonut! This programme is designed to help students visually explore the method for constructing non-expansive equivariant group operators (GENEOs) through the input of permutants and symmetrical functions.
+
+A GENEO, or non-expansive equivariant group operator, is a mathematical construct that can be applied to construct a new paradigm of learning networks, based on the formal study of the topological space of these operators. 
+
+Equivariance refers to the property of a function or operator that remains unchanged when applied to a transformed version of its input. In other words, if a function or operator is equivariant, it will give the same output no matter how its input is transformed.
+
+Non-expansiveness, on the other hand, refers to the property of a function or operator that does not increase the distance between its inputs. This property is important for ensuring that the output of the function or operator is not significantly different from its input, which can be useful for tasks such as learning or optimization.
+
+GENEOs are useful in the construction of learning networks, as they can be used to create models that are robust to transformations of their input data. They are also useful for studying the topological space of group operators, which can provide insights into the structure of data and the relationships between different data points.
+
+References
+
+    Non-Expansive Equivariant Group Operators for Artificial Intelligence
+
+Programme Features
+
+    Select groups and permutants
+    Insert symmetrical functions
+    Process images from input data
+    Save and reuse the GENEO as an image for further studies
+    Normalize the GENEO obtained by an arbitrary constant
+
+Technologies Used
+
+    Tauri
+    Rust
+    Vue.js
+    Vite.js
+    [ml-matrix]([url](https://mljs.github.io/matrix/))
+
+Contributions
+
+We welcome contributions to the program. If you have any suggestions or find any bugs, please open an issue or submit a pull request.
+
+
+Thank you for using the GDount Programme!