This document discusses theorems related to linear transformations between finite-dimensional vector spaces. It proves two main theorems:
1) A linear transformation T is invertible if and only if T maps a basis of the domain space V to a basis of the codomain space W.
2) A linear transformation T between vector spaces of equal dimension is invertible, injective, surjective, and maps bases to bases. These properties are shown to be equivalent.
The document provides a detailed proof of each theorem with examples to illustrate the concepts. It discusses key ideas such as linear independence, spanning sets, and the relationship between invertibility, injectivity and surjectivity of linear transformations.
Dyadics algebra.
Please send comments and suggestions to solo.hermelin@gmail.com. Thanks.
For more presentations on different subjects visit my website at http://www.solohermelin.com.
First part of description of Matrix Calculus at Undergraduate in Science (Math, Physics, Engineering) level.
Please send comments and suggestions to solo.hermelin@gmail.com.
For more presentations please visit my website at
http://www.solohermelin.com.
Differential Geometry for Machine LearningSEMINARGROOT
References:
Differential Geometry of Curves and Surfaces, Manfredo P. Do Carmo (2016)
Differential Geometry by Claudio Arezzo
Youtube: https://youtu.be/tKnBj7B2PSg
What is a Manifold?
Youtube: https://youtu.be/CEXSSz0gZI4
Shape analysis (MIT spring 2019) by Justin Solomon
Youtube: https://youtu.be/GEljqHZb30c
Tensor Calculus
Youtube: https://youtu.be/kGXr1SF3WmA
Manifolds: A Gentle Introduction,
Hyperbolic Geometry and Poincaré Embeddings by Brian Keng
Link: http://bjlkeng.github.io/posts/manifolds/,
http://bjlkeng.github.io/posts/hyperbolic-geometry-and-poincare-embeddings/
Statistical Learning models for Manifold-Valued measurements with application to computer vision and neuroimaging by Hyunwoo J.Kim
Dyadics algebra.
Please send comments and suggestions to solo.hermelin@gmail.com. Thanks.
For more presentations on different subjects visit my website at http://www.solohermelin.com.
First part of description of Matrix Calculus at Undergraduate in Science (Math, Physics, Engineering) level.
Please send comments and suggestions to solo.hermelin@gmail.com.
For more presentations please visit my website at
http://www.solohermelin.com.
Differential Geometry for Machine LearningSEMINARGROOT
References:
Differential Geometry of Curves and Surfaces, Manfredo P. Do Carmo (2016)
Differential Geometry by Claudio Arezzo
Youtube: https://youtu.be/tKnBj7B2PSg
What is a Manifold?
Youtube: https://youtu.be/CEXSSz0gZI4
Shape analysis (MIT spring 2019) by Justin Solomon
Youtube: https://youtu.be/GEljqHZb30c
Tensor Calculus
Youtube: https://youtu.be/kGXr1SF3WmA
Manifolds: A Gentle Introduction,
Hyperbolic Geometry and Poincaré Embeddings by Brian Keng
Link: http://bjlkeng.github.io/posts/manifolds/,
http://bjlkeng.github.io/posts/hyperbolic-geometry-and-poincare-embeddings/
Statistical Learning models for Manifold-Valued measurements with application to computer vision and neuroimaging by Hyunwoo J.Kim
A derivation of the Schwarzchild solution is presented with all relevant information. I have used this slides to teach Schwarzchild solution at my youtube channel. Here is the link
https://www.youtube.com/watch?v=ixhgvnGQZHM&t=1635s
Matrix Transformations on Some Difference Sequence SpacesIOSR Journals
The sequence spaces 𝑙∞(𝑢,𝑣,Δ), 𝑐0(𝑢,𝑣,Δ) and 𝑐(𝑢,𝑣,Δ) were recently introduced. The matrix classes (𝑐 𝑢,𝑣,Δ :𝑐) and (𝑐 𝑢,𝑣,Δ :𝑙∞) were characterized. The object of this paper is to further determine the necessary and sufficient conditions on an infinite matrix to characterize the matrix classes (𝑐 𝑢,𝑣,Δ ∶𝑏𝑠) and (𝑐 𝑢,𝑣,Δ ∶ 𝑙𝑝). It is observed that the later characterizations are additions to the existing ones
Left and Right Folds- Comparison of a mathematical definition and a programm...Philip Schwarz
We compare typical definitions of the left and right fold functions, with their mathematical definitions in Sergei Winitzki’s upcoming book: The Science of Functional Programming.
Errata:
Slide 13: "The way 𝑓𝑜𝑙𝑑𝑙 does it is by associating to the right" - should, of course ,end in "to the left".
Some Common Fixed Point Results for Expansive Mappings in a Cone Metric SpaceIOSR Journals
The purpose of this work is to extend and generalize some common fixed point theorems for Expansive type mappings in complete cone metric spaces. We are attempting to generalize the several well- known recent results. Mathematical subject classification; 54H25, 47H10
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
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Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
1. CAPÍTULO III
MATRIZ ASOCIADA A UNA TRANSFORMACIÓN LINEAL.
CONTENIDO:
3.1 Matriz asociada a una transformación lineal.
3.2 Algebra de transformaciones lineales.
3.3 Composición de Transformaciones lineales.
3.4 Transformaciones lineales invertibles.
3.5 Teorema de equivalencias de una transformación lineal.
3.6 Isomorfismo inducido por una transformación lineal.
3.7 Cambio de base y semejanza de matrices.
3.8 Producto Interno. Definición. Teoremas de caracterización.
3.9 Norma de un Vector.
3.10 Ortogonalidad. Conjunto ortogonal y conjunto ortonormal.
3.11 Proceso de ortogonalidad de Gram Schmitdt.
3.12 Espacio Dual de un espacio vectorial.
3.13 Adjunta de una transformación lineal
2. 88
3.5 TEOREMAS DE EQUIVALENCIAS DE UNA TRANSFORMACIÓN LINEAL.
TEOREMA 1.Sean (𝑉; 𝐾; +; ∙),(𝑊;𝐾;+; ∙) espaciosvectoriales de dimensión finitay 𝑇:𝑉 → 𝑊
una transformaciónlineal entonces, 𝑇 es invertible 𝑇 transforma una base de 𝑉 en una base
de 𝑊.
Demostración.
() Si 𝑇 es invertible 𝑇 transforma una base de 𝑉 en una base de 𝑊. ¡Probar!
Sea [𝑣] = {𝑣1;𝑣2;…; 𝑣𝑛} una base de 𝑉 y sean 𝑤1 = 𝑇(𝑣1); 𝑤2 = 𝑇(𝑣2);…; 𝑤𝑛 = 𝑇(𝑣𝑛) sus
imágenes.
Es decir {𝑤1;𝑤2;… ;𝑤𝑛}es una base de 𝑊. ¡Probar!
(i) El conjunto {𝑤1;𝑤2;…; 𝑤𝑛}es linealmente independiente.
Sea 𝑐1𝑤1 + 𝑐2𝑤2 + ⋯+ 𝑐𝑛𝑤𝑛 = 0𝑊 𝑐1 = 𝑐2 = ⋯ = 𝑐𝑛 = 0 ¡Probar!
Aplicando 𝑇−1, dado que 𝑇 es invertible y además es una transformación lineal:
𝑇−1(𝑐1𝑤1 + 𝑐2𝑤2 + ⋯+ 𝑐𝑛𝑤𝑛) = 𝑇−1(0𝑊)
𝑐1𝑇−1(𝑤1) + 𝑐2𝑇−1(𝑤2) + ⋯+ 𝑐𝑛𝑇−1(𝑤𝑛) = 𝑇−1(0𝑊)
𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛 = 0𝑉 y como {𝑣1;𝑣2;… ;𝑣𝑛}es una base de 𝑉
𝑐1 = 𝑐2 = ⋯ = 𝑐𝑛 = 0
Por lo tanto, el conjunto {𝑤1;𝑤2;… ;𝑤𝑛}es linealmente independiente.
(ii) El conjunto [𝑤] = {𝑤1;𝑤2;…;𝑤𝑛} genera al espacio 𝑊, es decir 𝐿{[𝑤]} = 𝑊
Sea cualquiera 𝑤 ∈ 𝑊 𝑇−1(𝑤) = 𝑣 ∈ 𝑉 𝑇−1(𝑤) = 𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛
Aplicando 𝑇: 𝑇[𝑇−1(𝑤)] = 𝑇(𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛)
𝑤 = 𝑇(𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛) = 𝑐1𝑇(𝑣1) + 𝑐2𝑇(𝑣2) + ⋯+ 𝑐𝑛𝑇(𝑣𝑛)
𝑤 = 𝑐1𝑤1 + 𝑐2𝑤2 + ⋯+ 𝑐𝑛𝑤𝑛 (a 𝑤 se le puede escribir en C. L. de la base [𝑤])
Por lo tanto, {𝑤1;𝑤2;… ;𝑤𝑛}genera al espacio 𝑊.
De (i) y (ii) el conjunto {𝑤1;𝑤2;…; 𝑤𝑛}es una base de 𝑊.
() Si 𝑇 transforma una base de 𝑉 en una base de 𝑊 𝑇 es invertible ¡Probar!
3. 89
(Es decir, debe existir 𝑇−1:𝑊 → 𝑉 tal que 𝑇−1𝑜𝑇 = 𝐼𝑉 y 𝑇𝑜𝑇−1 = 𝐼𝑊) ¡Probar!
Defínase la transformación lineal 𝐹:𝑊 → 𝑉 tal que 𝐹(𝑤𝑖) = 𝑣𝑖, ∀ 𝑖 = 1;2; …;𝑛 por el teorema
fundamental de las transformaciones lineales.
i) Probar que 𝐹𝑜𝑇 = 𝐼𝑉 .
Sea 𝑣 ∈ 𝑉 𝑣 = 𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛
(𝐹𝑜𝑇)(𝑣) = 𝐹[𝑇(𝑣)] =𝐹[𝑇(𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛)]
= 𝐹[𝑐1𝑇(𝑣1) + 𝑐2𝑇(𝑣2)+ ⋯+ 𝑐𝑛𝑇(𝑣𝑛)]pues 𝑇 es transformación lineal.
= 𝐹(𝑐1𝑤1 + 𝑐2𝑤2 + ⋯+ 𝑐𝑛𝑤𝑛)
= 𝑐1𝐹(𝑤1) + 𝑐2𝐹(𝑤2)+ ⋯+ 𝑐𝑛𝐹(𝑤𝑛)pues 𝐹 es transformación lineal.
= 𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛 = 𝑣 ∈ 𝑉 (𝐹𝑜𝑇)(𝑣) = 𝑣 = 𝐼(𝑣)
𝐹 𝑜 𝑇 = 𝐼𝑉 es la identidad en el espacio vectorial 𝑉.
ii) Probar que 𝑇𝑜𝐹 = 𝐼𝑊.
Sea 𝑤 ∈ 𝑊 𝑤 = 𝑐1𝑤1 + 𝑐2𝑤2 + ⋯+ 𝑐𝑛𝑤𝑛
(𝑇𝑜𝐹)(𝑤) = 𝑇[𝐹(𝑤)]=𝑇[𝐹(𝑐1𝑤1 + 𝑐2𝑤2 + ⋯+ 𝑐𝑛𝑤𝑛)]
= 𝑇[𝑐1𝐹(𝑤1) + 𝑐2𝐹(𝑤2)+ ⋯+ 𝑐𝑛𝐹(𝑤𝑛)]pues 𝐹 es una transformación lineal.
= 𝑇(𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛)
= 𝑐1𝑇(𝑣1) + 𝑐2𝑇(𝑣2)+ ⋯+ 𝑐𝑛𝑇(𝑣𝑛)pues 𝑇 es una transformación lineal.
= 𝑐1𝑤1 + 𝑐2𝑤2 + ⋯+ 𝑐𝑛𝑤𝑛 = 𝑤 ∈ 𝑊 (𝑇𝑜𝐹)(𝑤) = 𝑤 = 𝐼(𝑤)
𝑇 𝑜 𝐹 = 𝐼𝑊 es la identidad en el espacio vectorial 𝑊.
Luego de (i) y (ii) 𝑇 es invertible siendo la transformación lineal 𝐹 su inversa.
Es decir: 𝐹 = 𝑇−1.
Por lo tanto , de () y () el teorema queda demostrado.
EJEMPLO. Sea la transformación lineal 𝑇: 𝑅2 → 𝑃≤1definida por 𝑇(𝑎; 𝑏) = 2𝑎 − 𝑏𝑥, y sea [𝑣] =
{(1;−1); (2;3)} dos vectores de 𝑅2.
a) Mostrar que [𝑣] = {(1;−1);(2;3)} una base de 𝑅2.
4. 90
b) Mostrar que 𝑇([𝑣]) = {𝑇(1; −1);𝑇(2; 3)} una base de 𝑃≤1.
Solución.
a) i) [𝑣] = {(1;−1);(2;3)} es L. I., pues:
𝑐1(1;−1) + 𝑐2(2;3) = (0; 0) (𝑐1 + 2𝑐2;−𝑐1 + 3𝑐2) = (0;0) {
𝑐1 + 2𝑐2 = 0
−𝑐1 + 3𝑐2 = 0
𝑐1 = 𝑐2 = 0 .
ii) [𝑣] = {(1;−1);(2;3)} genera al espacio 𝑅2, pues:
Para todo (𝑥;𝑦) ∈ 𝑅2 debe existir 𝑐1 y 𝑐2 tal que (𝑥; 𝑦) = 𝑐1(1; −1) + 𝑐2(2;3)
(𝑥;𝑦) = (𝑐1 + 2𝑐2;−𝑐1 + 3𝑐2) {
𝑐1 + 2𝑐2 = 𝑥
−𝑐1 + 3𝑐2 = 𝑦
{
5𝑐2 = 𝑥 + 𝑦
−𝑐1 + 3𝑐2 = 𝑦
{
𝑐1 =
3𝑥−2𝑦
5
𝑐2 =
3𝑥−2𝑦
5
(𝑥;𝑦) =
3𝑥−2𝑦
5
(1; −1) +
3𝑥−2𝑦
5
(2;3) 𝑅2 = 𝐿{[𝑣]}
b) Mostrar que 𝑇([𝑣]) = {𝑇(1; −1);𝑇(2; 3)} una base de 𝑃≤1.
i) 𝑇([𝑣]) = {2 + 𝑥;4 − 3𝑥} es L. I., pues
𝑐1(2 + 𝑥) + 𝑐2(4 − 3𝑥) = 0 + 0𝑥 (2𝑐1 + 4𝑐2)+ (𝑐1 − 3𝑐2)𝑥 = 0 + 0𝑥
{
2𝑐1 + 4𝑐2 = 0
𝑐1 − 3𝑐2 = 0
{
2𝑐1 + 4𝑐2 = 0
−2𝑐1 + 6𝑐2 = 0
𝑐1 = 𝑐2 = 0
ii) 𝑇([𝑣]) = {2 + 𝑥;4 − 3𝑥} genera al espacio 𝑃≤1, pues:
Para todo 𝑎 + 𝑏𝑥 ∈ 𝑃≤1 debe existir 𝑐1 y 𝑐2 tal que 𝑎 + 𝑏𝑥 = 𝑐1(2 + 𝑥) + 𝑐2(4− 3𝑥)
𝑎 + 𝑏𝑥 = (2𝑐1 + 4𝑐2)+ (𝑐1 − 3𝑐2)𝑥 {
2𝑐1 + 4𝑐2 = 𝑎
𝑐1 − 3𝑐2 = 𝑏
{
2𝑐1 + 4𝑐2 = 𝑎
−2𝑐1 + 6𝑐2 = −2𝑏
{
𝑐1 =
3𝑎+4𝑏
10
𝑐2 =
𝑎−2𝑏
10
𝑎 + 𝑏𝑥 =
3𝑎+4𝑏
10
(2 + 𝑥) +
𝑎−2𝑏
10
(4 − 3𝑥)
𝑅2 = 𝐿{𝑇[𝑣]}
𝑇 es invertible.
TEOREMA 2. Sea 𝑇: 𝑉 → 𝑊 una transformación lineal entre dos espacios vectoriales de igual
dimensión; entonces las siguientes afirmaciones son equivalentes:
5. 91
a) 𝑇 es invertible. b) 𝑇 es inyectiva.
c) 𝑇 es sobreyectiva. d) 𝑇 Transforma bases de 𝑉 en bases de 𝑊.
Demostración.
a b
d c
(a b) Si 𝑇 es invertible 𝑇 es inyectiva.
Si 𝑇 es invertible (existe 𝑇−1; 𝑇−1(𝑤) = 𝑣, 𝑇𝑜𝑇−1 = 𝐼𝑊,𝑇−1𝑜𝑇 = 𝐼𝑉)
Se tiene que 𝑇(𝑢) = 𝑇(𝑣) 𝑢 = 𝑣 ¡Probar!
Si 𝑇(𝑢) = 𝑇(𝑣) 𝑇−1[𝑇(𝑢)] = 𝑇−1[𝑇(𝑣)] 𝑢 = 𝑣
𝑇 es inyectiva.
(b c) Si 𝑇 es inyectiva 𝑇 es sobreyectiva.
Siendo 𝑇 es inyectiva y siendo {𝑣1; 𝑣2;…;𝑣𝑛}𝑉 una base de 𝑉
{𝑇(𝑣1);𝑇(𝑣2);… ;𝑇(𝑣𝑛)} es linealmente independiente en 𝑊 y como 𝐷𝑖𝑚(𝑊) = 𝑛
{𝑇(𝑣1);𝑇(𝑣2);… ;𝑇(𝑣𝑛)} es una base para 𝑊.
Ahora sea cualquier 𝑤 ∈ 𝑊 ∃ 𝑣 ∈ 𝑉 tal que 𝑇(𝑣) = 𝑤. ¡Probar!
En efecto, sea 𝑤 = 𝑐1𝑤1 + 𝑐2𝑤2 + ⋯+ 𝑐𝑛𝑤𝑛 ∃ 𝑣 ∈ 𝑉 con 𝑣 = 𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛 tal
que
𝑇(𝑣) = 𝑇(𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛)= 𝑐1𝑇(𝑣1) + 𝑐2𝑇(𝑣2) + ⋯+ 𝑐𝑛𝑇(𝑣𝑛)
= 𝑐1𝑤1 + 𝑐2𝑤2 + ⋯+ 𝑐𝑛𝑤𝑛 = 𝑤 ∈ 𝑊, como 𝑇 es inyectiva 𝑣 es único.
𝑇 es sobreyectiva.
Recordar: T es inyectiva si 𝑢 ≠ 𝑣 𝑇(𝑢) ≠ 𝑇(𝑣)
(c d) Si 𝑇 es sobreyectiva T transforma bases de 𝑉 en bases de 𝑊 .
Siendo 𝑇 es sobreyectiva y siendo {𝑣1;𝑣2;…; 𝑣𝑛} una base de 𝑉, y que 𝑇(𝑣𝑖) = 𝑤𝑖, ∀ 𝑖 =
1;2;…; 𝑛
{𝑤1;𝑤2;…; 𝑤𝑛}es una base para 𝑊 ¡Probar!
6. 92
En efecto:
∀ 𝑤 ∈ 𝑊 existe 𝑣 ∈ 𝑉 con 𝑣 = 𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛 tal que
𝑇(𝑣) = 𝑇(𝑐1𝑣1 + 𝑐2𝑣2 + ⋯+ 𝑐𝑛𝑣𝑛)= 𝑐1𝑇(𝑣1) + 𝑐2𝑇(𝑣2)+ ⋯+ 𝑐𝑛𝑇(𝑣𝑛)
=𝑐1𝑤1 + 𝑐2𝑤2 + ⋯+ 𝑐𝑛𝑤𝑛 = 𝑤 por ser 𝑇 sobreyectiva.
Por otro lado, como 𝐷𝑖𝑚(𝑊) = 𝑛 {𝑤1;𝑤2;…; 𝑤𝑛}es una base para 𝑊.
𝑇 transforma bases de 𝑉 en bases de 𝑊.
(d a) Si 𝑇 transforma bases de 𝑉 en bases de 𝑊 𝑇 es invertible. ¡Probar!
Está probado en el Teorema anterior.
EJERCICIO. Probar el Teorema en dirección inversa.
a b
d c
EJEMPLO. Aplique el teorema al ejemplo siguiente. Sea 𝑇: 𝑅2 → 𝑅2 tal que 𝑇 [
𝑥
𝑦] = [
𝑎 𝑏
𝑐 𝑑
] [
𝑥
𝑦]
Solución.
𝑇 es invertible 𝑇 es inyectiva
𝑇 es sobreyectiva 𝑇 Transforma bases de 𝑉 en bases de 𝑊
(a b) Si 𝑇 es invertible 𝑇 es inyectiva.
∀ [
𝑥
𝑦] , [
𝑧
𝑤
] ∈ 𝑅2, si 𝑇 [
𝑥
𝑦] = 𝑇 [
𝑧
𝑤
] [
𝑎 𝑏
𝑐 𝑑
] [
𝑥
𝑦] = [
𝑎 𝑏
𝑐 𝑑
][
𝑧
𝑤
] [
𝑎𝑥 + 𝑏𝑦
𝑐𝑥 + 𝑑𝑦
] = [
𝑎𝑧 + 𝑏𝑤
𝑐𝑧 + 𝑑𝑤
]
{
𝑎𝑥 + 𝑏𝑦 = 𝑎𝑧 + 𝑏𝑤
𝑐𝑥 + 𝑑𝑦 = 𝑐𝑧 + 𝑑𝑤
i)
−𝑐
𝑎
{
𝑎(𝑥 − 𝑧) + 𝑏(𝑦 − 𝑤) = 0
𝑐(𝑥 − 𝑧) + 𝑑(𝑦 − 𝑤) = 0
{
−𝑎𝑐(𝑥 − 𝑧) − 𝑏𝑐(𝑦 − 𝑤) = 0
𝑎𝑐(𝑥 − 𝑧) + 𝑎𝑑(𝑦 − 𝑤) = 0
(𝑦 − 𝑤)(𝑎𝑑 − 𝑏𝑐) = 0 {
(𝑦 − 𝑤) = 0
𝑜 (𝑎𝑑 − 𝑏𝑐) = 0
7. 93
𝑦 = 𝑤 , pues 𝐷𝑒𝑡(𝐴) = 𝑎𝑑 − 𝑏𝑐 ≠ 0 , pues es invertible.
ii) Del mismo modo 𝑥 = 𝑧 [
𝑥
𝑦] = [
𝑧
𝑤
]
𝑇 es inyectiva.
(b c) Si 𝑇 es inyectiva 𝑇 es sobreyectiva.
∀ [
𝑚
𝑛
] ∈ 𝑅2, de llegada ∃[
𝑥
𝑦] ∈ 𝑅2, de partida tal que 𝑇 [
𝑥
𝑦] = [
𝑚
𝑛
]
𝐴 [
𝑥
𝑦] = [
𝑚
𝑛
] [
𝑥
𝑦] = 𝐴−1[
𝑚
𝑛
] , [
𝑥
𝑦] es único pues 𝑇 es inyectiva.
Si existe otro [
𝑧
𝑤
] ∈ 𝑅2 tal que 𝑇[
𝑧
𝑤
] = [
𝑚
𝑛
] 𝐴[
𝑧
𝑤
] = [
𝑚
𝑛
] [
𝑧
𝑤
] = 𝐴−1 [
𝑚
𝑛
]
Pero como 𝑇 inyectiva [
𝑥
𝑦] = [
𝑧
𝑤
]
𝑇 es sobreyectiva.
(c d) Si 𝑇 es sobreyectiva 𝑇 transforma bases de 𝑉 en bases de 𝑊 .
Sea [𝑣] = [𝑣1;𝑣2] = {[
𝑎
𝑏
] , [
𝑐
𝑑
]} una base de 𝑉
Como 𝑇 es sobreyectiva ∀ 𝑤 = [
𝑚
𝑛
] ∈ 𝑅2 de llegada, ∃ 𝑣 = [
𝑥
𝑦] = 𝑐1 [
𝑎
𝑏
] + 𝑐2 [
𝑐
𝑑
] ∈ 𝑅2 de
partida, tal que
𝑇[
𝑥
𝑦] = 𝑇 (𝑐1 [
𝑎
𝑏
] + 𝑐2 [
𝑐
𝑑
]) = 𝑐1𝑇[
𝑎
𝑏
] + 𝑐2𝑇[
𝑐
𝑑
] = 𝑐1 [
𝑝
𝑞] + 𝑐2[
𝑟
𝑠
] = [
𝑚
𝑛
]
Como 𝑇 es inyectiva, si [
𝑎
𝑏
] ≠ [
𝑐
𝑑
] 𝑇 [
𝑎
𝑏
] ≠ 𝑇[
𝑐
𝑑
] [
𝑝
𝑞] ≠ [
𝑟
𝑠
]
Por lo tanto, [𝑢] = {𝑤1;𝑤2} = {[
𝑝
𝑞] ; [
𝑟
𝑠
]} es una base de 𝑅2 de llegada.
(d a) 𝑇 transforma bases de 𝑉 en bases de 𝑊 𝑇 es invertible.
Sea la base [𝑣] = {[
𝑥
𝑦] ,[
𝑧
𝑤
]} de 𝑅2 entonces [𝑤] = {𝑇 [
𝑥
𝑦] , 𝑇[
𝑧
𝑤
]} es una base de 𝑊.
i) 𝑇 es inyectiva, pues [
𝑥
𝑦] ≠ [
𝑧
𝑤
] 𝑇[
𝑥
𝑦] ≠ 𝑇[
𝑧
𝑤
] 𝐴 [
𝑥
𝑦] ≠ 𝐴 [
𝑧
𝑤
] Entonces T es inyectiva.
ii) 𝑇 es sobreyectiva, pues ∀[
𝑎 𝑏
𝑐 𝑑
] [
𝑥
𝑦] , ∃[
𝑚
𝑛
] ∈ 𝑅2 tal que 𝑇[
𝑚
𝑛
] = [
𝑎 𝑏
𝑐 𝑑
] [
𝑥
𝑦]
8. 94
iii) Dado que 𝐷𝑒𝑡(𝐴) = 𝑎𝑑 − 𝑏𝑐 ≠ 0 y si 𝑇[
𝑥
𝑦] = 𝐴 [
𝑥
𝑦] 𝑇−1(𝑇 [
𝑥
𝑦]) = 𝑇−1 (𝐴 [
𝑥
𝑦])
Si 𝐴 = [
𝑎 𝑏
𝑐 𝑑
] 𝐴−1 =
1
𝑎𝑑−𝑏𝑐
[
𝑑 −𝑏
−𝑐 𝑎
]
𝑇−1[
𝑝
𝑞] = 𝐴−1 [
𝑝
𝑞] =
1
𝑎𝑑−𝑏𝑐
[
𝑑 −𝑏
−𝑐 𝑎
][
𝑝
𝑞]
EJEMPLO 2. Aplique el teorema al ejemplo siguiente. Sea 𝑇:𝑅2 → 𝑅2 tal que 𝑇(𝑥;𝑦) = (3𝑥; −𝑦)
Solución. Ejercicio.
𝑅2 ≈ 𝑃≤1 ≈ 𝑀2×1 ≈ 𝐶
3.6 ISOMORFISMO INDUCIDO POR UNA TRANSFORMACIÓN LINEAL .
TEOREMA. Sean (𝑉;𝐾;+; ∙) y (𝑊;𝐾;+;∙)espacios vectoriales sobre el campo 𝐾, sea 𝑇:𝑉 → 𝑊
una transformación lineal y sea :𝑉 → 𝑉 𝑁(𝑇)
⁄ definida por (𝑣) = 𝑣 + 𝑁(𝑇) la proyección
canónica, entonces:
a) Existe una única transformación lineal 𝑇∗:𝑉 𝑁(𝑇)
⁄ → 𝑊 tal que 𝑇∗𝑜 = 𝑇
b) 𝑉 𝑁(𝑇)
⁄ ≅ 𝐼𝑚(𝑇): es decir que 𝑉 𝑁(𝑇)
⁄ es aproximadamente igual a 𝐼𝑚(𝑇)
En el teorema 𝑁(𝑇) el núcleo de 𝑇, y 𝑉 𝑁(𝑇)
⁄ es el espacio cociente de 𝑉 sobre 𝑁(𝑇).
Prueba.
a) Se define 𝑇∗:𝑉 𝑁(𝑇)
⁄ → 𝑊 por 𝑇∗(𝑣 + 𝑁(𝑇)) = 𝑇(𝑣)
i) Se probará que 𝑇∗ está bien definida; es decirque 𝑇∗ no depende del elemento representante
de la clase 𝑣 + 𝑁(𝑇) ∈ 𝑉 𝑁(𝑇)
⁄
Sean 𝑣1 + 𝑁(𝑇) y 𝑣2 + 𝑁(𝑇) ∈ 𝑉 𝑁(𝑇)
⁄
Si 𝑣1 + 𝑁(𝑇) = 𝑣2 + 𝑁(𝑇) 𝑣1 = 𝑣2 𝑣1 − 𝑣2 = 0𝑉
𝑣1 − 𝑣2 ∈ 𝑁(𝑇) 𝑇(𝑣1 − 𝑣2) = 0𝑊
𝑇(𝑣1) − 𝑇(𝑣2) = 0𝑊 𝑇(𝑣1) = 𝑇(𝑣2) 𝑇∗(𝑣1 + 𝑁(𝑇)) = 𝑇∗(𝑣2 + 𝑁(𝑇))
𝑉 𝑁(𝑇)
⁄
𝑊
𝑉
𝑇∗
𝑇 = 𝑇∗𝑜
𝑇
9. 95
Por lo tanto, 𝑇∗ está bien definida.
ii) 𝑇∗ es una transformación lineal.
En efecto.
𝑇∗[𝑟(𝑣1 + 𝑁(𝑇)) + 𝑡(𝑣2 + 𝑁(𝑇))]= 𝑇∗[(𝑟𝑣1 + 𝑁(𝑇)) + (𝑡𝑣2 + 𝑁(𝑇))]
= 𝑇∗[(𝑟𝑣1 + 𝑡𝑣2) + 𝑁(𝑇)] = 𝑇(𝑟𝑣1 + 𝑡𝑣2) = 𝑟𝑇(𝑣1) + 𝑡𝑇(𝑣2)
= 𝑟 𝑇∗(𝑣1 + 𝑁(𝑇)) + 𝑡 𝑇∗(𝑣2 + 𝑁(𝑇))
Por lo tanto, 𝑇∗ es una transformación lineal sobre el campo 𝐾.
iii) 𝑇∗𝑜 = 𝑇 ¡Probar!
En efecto.
(𝑇∗𝑜 )(𝑣) = 𝑇∗((𝑣)) = 𝑇∗(𝑣 + 𝑁(𝑇)) = 𝑇(𝑣)
Porlo tanto, 𝑇∗𝑜 = 𝑇
iv) La unicidad.
Supongamos que existe otra transformación lineal 𝑈∗:𝑉 𝑁(𝑇)
⁄ → 𝑊 con las mismas
propiedades que 𝑇∗.
𝑈∗(𝑣+ 𝑁(𝑇)) = 𝑇(𝑣) = 𝑇∗(𝑣+ 𝑁(𝑇)) 𝑈∗ = 𝑇∗
b) Se cumple que 𝑉 𝑁(𝑇)
⁄ ≅ 𝐼𝑚(𝑇)
Es decir, se probará que la aplicación 𝑇∗:𝑉 𝑁(𝑇)
⁄ → 𝐼𝑚(𝑇)es un isomorfismo.
i) 𝑇∗ es un monomorfismo (𝑇∗ es inyectiva).
En efecto:
𝑁(𝑇∗) = {𝑣 + 𝑁(𝑇) 𝑇∗(𝑣 + 𝑁(𝑇)) = 0𝑊
⁄ }
𝑁(𝑇∗) = {𝑣 + 𝑁(𝑇) 𝑇(𝑣) = 0𝑊
⁄ }
𝑁(𝑇∗) = {𝑣 + 𝑁(𝑇) 𝑣 ∈ 𝑁(𝑇)
⁄ }
𝑁(𝑇∗) = 𝑁(𝑇)
“𝑁(𝑇) es el cero del espacio cociente 𝑉 𝑁(𝑇)
⁄ ”
Por lo tanto, 𝑇∗ es un monomorfismo.
10. 96
ii) 𝑇∗ es un epimorfismo (𝑇∗ es sobreyectiva).
En efecto:
𝐼𝑚(𝑇∗) = {𝑇∗(𝑣+ 𝑁(𝑇)) 𝑣 ∈ 𝑉
⁄ } = {𝑇(𝑣) 𝑣 ∈ 𝑉
⁄ }= 𝐼𝑚(𝑇)
Por lo tanto, 𝑇∗ es un epimorfismo.
Finalmente, de (i) y (ii) 𝑇∗ es un isomorfismo.
EJEMPLO 1. Sea la transformación lineal 𝑇: 𝑅2 → 𝑅2 definido por 𝑇(𝑥; 𝑦) = (3𝑥 − 𝑦;𝑥 + 2𝑦).
Hallar el núcleo de 𝑇 y el isomorfismo inducido por 𝑇.
Solución.
i) Hallando el núcleo de la transformación lineal
𝑁(𝑇) = {(𝑥;𝑦) ∈ 𝑅2 𝑇(𝑥;𝑦) = (0;0)
⁄ } = {(𝑥;𝑦) ∈ 𝑅2 (3𝑥 − 𝑦;𝑥 + 2𝑦) = (0;0)
⁄ }
(3𝑥 − 𝑦;𝑥 + 2𝑦) = (0;0) {
3𝑥 − 𝑦 = 0
𝑥 + 2𝑦 = 0
{
6𝑥 − 2𝑦 = 0
𝑥 + 2𝑦 = 0
{
𝑥 = 0
𝑦 = 0
𝑁(𝑇) = (0; 0) 𝐷𝑖𝑚(𝑁(𝑇)) = 0
ii) Hallando el espacio cociente 𝑉 𝑊
⁄ = {[𝑣] = 𝑣 + 𝑤 𝑣 ∈ 𝑉𝑤 ∈ 𝑊
⁄ }
Con los datos del ejemplo: 𝑅2 𝑁(𝑇)
⁄ = {[𝑣] = 𝑣 + 𝑣 ∈ 𝑅2 ∈ 𝑁(𝑇)
⁄ }
𝑅2 𝑁(𝑇)
⁄ = {[𝑣] = 𝑣 + 0𝑉 𝑣 ∈ 𝑅2
⁄ }= {𝑣 𝑣 ∈ 𝑅2
⁄ }= 𝑅2.
Recordar que: 𝐷𝑖𝑚(𝑅2 {(0;0)}
⁄ ) = 𝐷𝑖𝑚(𝑅2)− 𝐷𝑖𝑚(𝑁(𝑇)) = 2 − 0 = 2
iii) Hallando el isomorfismo inducido: 𝑇∗
Aquí se tiene que = 𝐼𝑑𝑅2
Porotro lado, 𝑇∗:𝑅2 𝑁(𝑇)
⁄ → 𝑅2 𝑇∗:𝑅2 → 𝑅2 𝑇 = 𝑇∗
La transformación lineal adjunta será: 𝑇∗[(𝑥;𝑦) + 0𝑅2 ] = (3𝑥 − 𝑦;𝑥 + 2𝑦)
𝑇∗
𝑅2 𝑅2
𝑅2 𝑁(𝑇)
⁄
𝑇
𝑇∗
𝑅2 𝑅2
𝑅2
𝑇
11. 97
O también: 𝑇∗[(𝑥;𝑦) + 𝑁(𝑇)] = (3𝑥 − 𝑦;𝑥 + 2𝑦)
EJEMPLO 2. Sea la transformación lineal 𝑇: 𝑅2 → 𝑅2 definido por 𝑇(𝑥; 𝑦) = (0;0). Hallar el
núcleo de 𝑇 y el isomorfismo inducido por 𝑇.
Solución.
i) Hallando el núcleo de la transformación lineal
𝑁(𝑇) = {𝑣 ∈ 𝑉 𝑇(𝑣) = 0𝑊
⁄ }
𝑁(𝑇) = {(𝑥;𝑦) ∈ 𝑅2 𝑇(𝑥;𝑦) = (0;0)
⁄ } 𝑁(𝑇) = 𝑅2
ii) Hallando el espacio cociente 𝑉 𝑊
⁄ = {[𝑣] = 𝑣 + 𝑤 𝑣 ∈ 𝑉𝑤 ∈ 𝑊
⁄ }
Con los datos del ejemplo: 𝑅2 𝑅2
⁄ = {[𝑣] = 𝑣 + 𝑣 𝑣 ∈ 𝑅2 𝑣 ∈ 𝑅2
⁄ }
Usando la identidad 𝐷𝑖𝑚(𝑉 𝑊
⁄ ) = 𝐷𝑖𝑚(𝑉) − 𝐷𝑖𝑚(𝑊)
𝐷𝑖𝑚(𝑅2 𝑅2
⁄ ) = 𝐷𝑖𝑚(𝑅2) − 𝐷𝑖𝑚(𝑅2) = 0 𝐷𝑖𝑚(𝑅2 𝑅2
⁄ ) = 0 𝑅2 𝑅2
⁄ = {(0;0)}
iii) Hallando el isomorfismo inducido: 𝑇∗
Aquí se tiene que = (𝑥;𝑦) = (0;0)
Porotro lado, 𝑇∗:𝑅2 𝑅2
⁄ → 𝑅2 𝑇∗:{(0;0)} → 𝑅2
La transformación lineal adjunta será: 𝑇∗[(0;0) + 0𝑅2 ] = (0; 0)
O también: 𝑇∗[(0;0) + 𝑁(𝑇)] = (0; 0)
EJEMPLO 3. Sea la transformación lineal 𝑇:𝑅3 → 𝑅2 definida por 𝑇(𝑥;𝑦;𝑧) = (2𝑧 − 𝑦; 2𝑥 − 𝑧).
Determinar su núcleo de 𝑇 y el isomorfismo inducido por 𝑇.
Solución.
i) Hallando el núcleo.
𝑇∗
𝑅2 𝑅2
𝑅2 𝑅2
⁄
𝑇
𝑇∗
𝑅2 𝑅2
{(0;0)}
𝑇