Practice Question

Duration: 2 min

This video lesson is available to enrolled students.

Return to /learn/DSSSB-TGT-COMPUTER-SCIENCE-PAPER-2/design-analysis-of-algorithms/time-complexity-analysis/master-theorem/asset-practice-question-4693 after enrolling

Inside: a video lesson and guided study material.

Module outline

  1. About Course: About the Course
  2. Programming, Data Structures, OOP & Java: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling, Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing, Java, OOPS with C++, Java Fundamentals, Array, String, IO & References, Language Design, Intro to Compilers, Visual Basics, Syntax Analysis: Bottom-Up, Object Oriented Technology
  3. Computer Networks, TCP/IP & Network Security: Introduction to CN, Data Communication, DLL: Flow Control, DLL: Access Control, DLL: Error Control, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics, Network Access Technologies, Network Security, Society, Law & Ethics, Cloud Computing, Mobile Computing, Net Layer:Routing Protocol, Cyber Safety and Security
  4. Teaching Methodology: वृद्धि और विकास / Growth and Development, Concept of Pedagogy, विकास के सिद्धांत / Theories of Development, समावेशी शिक्षा / Inclusive Education, Experiential Pedagogy, आकलन और मूल्यांकन / Assessment and Evaluation, समाजीकरण और जेंडर / Socialisation and Gender, National Education Policy (NEP) 2020, संज्ञानात्मक प्रक्रियाएँ / Cognitive Processes, शिक्षण योजना और शिक्षण कौशल / Teaching Planning and Teaching Skills, Personality Development, शिक्षण विधियाँ / Teaching Methods, अधिगम और व्यवहारवादी सिद्धांत / Learning and Behavioural Theories, Learners & Learning Process, Factors Affecting Teaching, शिक्षण विधियाँ एवं उपागम / Teaching Methods and Approaches, शिक्षण-अधिगम प्रक्रिया एवं कक्षा प्रबंधन / Teaching-Learning Process and Classroom Management, शिक्षण सहायक सामग्री एवं शैक्षिक तकनीकी / Teaching Aids and Educational Technology, सूक्ष्म शिक्षण एवं कक्षा संप्रेषण / Microteaching and Classroom Communication, आकलन एवं मूल्यांकन / Assessment and Evaluation, पाठ्यचर्या, कला एवं सह-शैक्षिक क्षेत्र / Curriculum, Arts and Co-curricular Areas, दिव्यांग बच्चों की शिक्षा / Education of Children with Disabilities, शिक्षक: गुण, व्यावसायिक नैतिकता एवं विकास / Teacher: Qualities, Professional Ethics and Development
  5. Digital Electronics / Boolean Logic: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation, Analog-Digital Conversion
  6. Operating Systems & Linux: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, File Management, Disc Scheduling, Unix OS, Linux OS, Distributed Systems, Windows OS
  7. Data Base Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, Relational Algebra, SQL, File Organization & Indexing, Transaction Management, Concurrency Control, Database Security & Authorization, Database Recovery, Data Warehousing & Mining
  8. Internet & Web Technologies: Website, Browser & Services, Internet Fundamentals, Web Design & Development, Protocols & Services, Web Publishing & Hosting, Server Side & Security, HTML Basics, CSS, Emerging Technologies, JavaScript-Basics, .Net Programming, Electronic Data Interchange and E-Commerce, XML
  9. Computer Fundamentals, IT Basics & Architecture: Basics of COA, Cache Memory Organization, Input Output Organisation, Register Transfer and Microoperations, Control Unit Design, Programming the Basic Computer, Terms & Abbreviations, MS Office Applications, Instr Formats & Modes, Floating Point Rep, कंप्यूटर के मूल सिद्धांत / Computer Fundamentals, साइबर सुरक्षा / Cyber Safety and Security, कंप्यूटर सॉफ़्टवेयर / Computer Software, ऑपरेटिंग सिस्टम / Operating System, वर्ड प्रोसेसिंग (MS Word) / Word Processing (MS Word), कंप्यूटर नेटवर्क / Computer Networks, प्रेज़ेंटेशन (MS PowerPoint) / Presentation Software (MS PowerPoint)
  10. Python Language: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis
  11. Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management, extras, Fundamentals of Systems and Information Systems
  12. Design & Analysis of Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Advanced Algorithms
  13. Mathematics - I, II, III, IV: Permutation and Combination, Logarithm, Linear Algebra, Algebra, Calculus, Trigonometry, Vectors, Set Theory, Functions, Relations, Propositional and Predicate Logic, Research Process Steps, Graph Theory, समुच्चय, संबंध, फलन और विविक्त गणित / Sets, Relations, Functions and Discrete Mathematics, संख्या पद्धति और संख्या सिद्धांत / Number Systems and Number Theory, यूक्लिडीय ज्यामिति और क्षेत्रमिति / Euclidean Geometry and Mensuration, सांख्यिकी और प्रायिकता / Statistics and Probability, निर्देशांक ज्यामिति, सदिश और त्रिविमीय ज्यामिति / Coordinate Geometry, Vectors and 3D Geometry, बहुपद, समीकरण और सम्मिश्र संख्याएँ / Polynomials, Equations and Complex Numbers, समतल क्षेत्रमिति / Plane Mensuration, प्रतिचयन / Sampling, प्रतिशत / Percentage, सरलीकरण, घातांक और करणी / Simplification, Indices and Surds, अनुपात और समानुपात / Ratio and Proportion
  14. Computer Graphics, Multimedia & Mobile Computing: Basics of Computer Graphics, 2-D Geometrical Transforms and Viewing, 3-D Object Representation, Geometric Transformations and Viewing, Multimedia
  15. Emerging Trends: Emerging Tech Trends, Knowledge Representation, Natural Language Processing, व्यापार, विपणन एवं उपभोक्ता संरक्षण / Trade, Marketing and Consumer Protection
  16. Statistical Techniques: Probability, Statistics
  17. Interpolation - DI: आँकड़ा निर्वचन / Data Interpretation
  18. Basis of Physics: वैज्ञानिक उपलब्धियाँ और अनुसंधान / Scientific Achievements and Research
  19. Previous Year Paper:
  20. Business Studies and Management: Business Communication, प्रबंध के सिद्धांत एवं कार्य / Principles and Functions of Management, लेखांकन के आधार एवं लेन-देनों का अभिलेखन / Accounting Fundamentals and Recording of Transactions, Business Economics, ह्रास, अंतिम खाते व कंप्यूटरीकृत लेखांकन / Depreciation, Final Accounts and Computerised Accounting, Knowledge Management & New Economy
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video demonstrates solving the recurrence relation T(n) = 7T(n/2) + n^2 using the Master Theorem. The instructor identifies parameters a=7, b=2, and f(n)=n^2. He compares f(n) to n^(log_b a) and determines that Case 1 applies because the recursive part grows faster. The final solution is derived as Theta(n^(log_2 7)).

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor begins by presenting the recurrence relation T(n) = 7T(n/2) + n^2 on the screen. He writes the general Master Theorem form T(n) = a * T(n/b) + f(n) to structure the solution. He explicitly identifies the constants: a=7, b=2, and the function f(n) = n^2. Next, he calculates the term n^(log_b a), substituting the values to get n^(log_2 7). He then compares f(n) against this term to determine which case of the theorem applies. He writes the condition f(n) = O(n^(log_b a - epsilon)) and notes that since log_2 7 is approximately 2.8, which is greater than 2, the condition holds true for some epsilon > 0. This confirms that Case 1 is applicable.

  2. 2:00 – 2:08 02:00-02:08

    The instructor concludes the derivation by writing the final complexity class. He states that for Case 1, the solution is T(n) = Theta(n^(log_b a)). He substitutes the calculated exponent back into the formula, resulting in T(n) = Theta(n^(log_2 7)). He underlines this final expression to emphasize it as the answer to the problem.

This lecture segment provides a clear, step-by-step application of the Master Theorem for divide-and-conquer recurrences. The key takeaway is the systematic comparison between the work done at each level of recursion (f(n)) and the work done by the recursive calls (n^(log_b a)). By establishing that the recursive part dominates the non-recursive part, the instructor correctly identifies the asymptotic behavior of the algorithm. This method is crucial for analyzing the time complexity of algorithms like Strassen's matrix multiplication.

Loading lesson…