Non linear dynamical systems
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This document discusses nonlinear dynamical systems and modeling techniques. Nonlinear dynamical systems have multiple inputs, feedback loops, and sensitivity to initial conditions. They can be modeled using techniques like state space models, principal component analysis, neural networks, and chaos theory. Modeling nonlinear dynamical systems involves accounting for their emergent behavior from component interactions, distributed nature, and potential to evolve into chaotic states.
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- There are different types of ANNs that vary in their structure and learning methods, including multilayer perceptrons, convolutional neural networks, and recurrent neural networks. ANNs can perform tasks using supervised, unsupervised, or reinforcement learning.
- ANNs have many applications including face recognition, ridesharing, handwriting
Artificial Neural Network
- An artificial neural network (ANN) is a computational model inspired by biological neural networks in the brain. ANNs contain interconnected nodes that can learn relationships and patterns from data through a process of training.
- The basic ANN architecture includes an input layer, hidden layers, and an output layer. Information flows from the input to the output layers through the hidden layers as the network learns.
- There are different types of ANNs that vary in their structure and learning methods, including multilayer perceptrons, convolutional neural networks, and recurrent neural networks. ANNs can perform tasks like face recognition, prediction, and classification through supervised, unsupervised, or reinforcement learning.
- While ANNs have advantages like fault tolerance
Seminar on Chaos Based Cryptography
Slide Include
Introduction
Image encryption
Random Number Generation
Comparison of different techniques
Machine Learning, Stock Market and Chaos
Dr. Roitman discusses the use of Artificial Intelligence to solve complex and insoluble problems. Artificial intelligence approach is in the root of I Know First predictive algorithm.
Course Learning Outcomes Virtual Systems and Services
Introducing simulation models
Classifying simulation models
Approaching a simulation-based problem
Dynamical systems modeling
nil-100128213838-phpapp02.pptx
This document provides an overview of neural networks, including their biological inspiration, basic components like neurons and activation functions, different types of neural networks based on connection type, topology and learning method, and applications. It discusses how neural networks can learn from experience to improve performance and deal with incomplete information. The advantages are the ability to perform non-linear tasks and continue working if some elements fail, while disadvantages include the need for training and high processing times for large networks.
nil-100128213838-phpapp02.pdf
This document provides an overview of neural networks. It discusses how neural networks are inspired by biological neurons and are composed of interconnected processing units called neurons arranged in layers. There are different types of neural networks defined by their connection patterns, topology, and learning methods. Neural networks are applied to problems like pattern recognition, forecasting, and control systems. They have advantages like the ability to learn from data and handle incomplete information, but also disadvantages like requiring extensive training.
Neural Networks Lec3.pptx
- Artificial neural networks are inspired by biological neurons and are made up of artificial neurons (perceptrons).
- A perceptron receives multiple inputs, assigns weights to them, calculates the weighted sum, and passes it through an activation function to produce an output.
- Weights allow the perceptron to learn the importance of different inputs and change the orientation of the decision boundary. The bias helps shift the activation function curve.
- Common activation functions include sigmoid, tanh, ReLU, and leaky ReLU. They introduce non-linearity and help address issues like vanishing gradients.
The future is quantum
The slide discusses some basic information that I presented in my public talk titled "The future is quantum", at the Indian Institute of Science, Bengaluru, India.
In this slide, I have covered the basics of quantum computing and quantum communication.
Please write your suggestions to quantumaravinth@gmail.com. Looking forward to interacting with you
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The Hurricane's Butterfly: Debugging pathologically performing systems
Course Learning Outcomes Virtual Systems and Services
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Primer on major data mining algorithms
This document provides an overview of major data mining algorithms, including supervised learning techniques like decision trees, random forests, support vector machines, naive Bayes, and logistic regression. Unsupervised techniques discussed include clustering algorithms like k-means and EM, as well as association rule learning using the Apriori algorithm. Application areas and advantages/disadvantages of each technique are described. Libraries for implementing these algorithms in Python and R are also listed.
Vikram emerging technologies
These technologies are gradually reshaping the financial services industry:
- Artificial intelligence, deep learning, analytics, blockchain, and robotic process automation are emerging technologies applied in finance.
- Analytics has been a top technology trend for over a decade and is going through four stages from basic business intelligence to real-time streaming analytics.
- Blockchain uses distributed ledger technologies and consensus algorithms to securely record transactions in a decentralized manner, having applications for cryptocurrency, smart contracts, and identity management.
Blockchain concept explained
Blockchain is a distributed database that records transactions in blocks that are linked using cryptography. It uses consensus algorithms to ensure participants agree on the state of transactions and uses data structures like linked lists and Merkle trees to organize transactions. Blockchain was designed to maintain a consistent state across distributed systems in the presence of faults or failures.
Hyperloop explained
Hyperloop is a proposed high-speed transportation system that would use reduced pressure tubes and linear induction motors to propel passenger capsules at over 600 mph. Capsules would ride on a cushion of air within the tubes and be accelerated by linear induction motors powered by solar panels. Key advantages include using open source technology, being energy efficient and non-polluting, and employing linear induction motors which have no moving parts and propel the capsules through electromagnetic fields rather than friction.
Vikram budget 2018
The document summarizes the key highlights of the Indian government's 2018 budget. It outlines differences between government and business accounting, the major components of government expenditures and receipts, and defines fiscal deficit. It then details several new major expenditure initiatives in areas like agriculture, welfare, education, and healthcare. Other initiatives include infrastructure projects and reforms in taxation, banking, and markets. The analysis suggests the budget aims to boost growth through fiscal expansion and reforms while maintaining a fiscal deficit of 3.5% of GDP. It is expected to increase investment, employment, consumption, and GDP.
Vikram cgst updated budget 2018
The document provides an overview of key changes and definitions in the CGST Act related to Budget 2018. Some important points include:
- Chapter 1 covers introductory provisions including important definitions like casual taxable person, non-resident taxable person, composite supply, mixed supply, exempt supply, non-taxable supply, and goods and services.
- Chapter 2 deals with tax officers and their powers. Important officers include those appointed by the central and state governments.
- Chapter 3 covers levy and collection of tax including the scope and time of supply, tax liability on composite/mixed supplies, the charging section, reverse charge, and the composition scheme.
- Chapter 4 defines the time and value
Basic health facts presentation by vikram
The document provides information on various health and nutrition topics. It discusses that the human body needs over 100 vitamins and minerals to stay healthy, and balanced portions of protein, grains, and fruits and vegetables are important. Calorie needs vary by individual based on factors like lean mass and activity level. Therapeutic diets are prescribed to address specific health conditions. The body is 60-70% water and it is crucial to drink water daily to replace losses from activities. Exercise benefits include improved cardiovascular health, muscle building, weight loss, and reduced aging. Moderate exercise for 30 minutes daily is recommended. The effects of exercise on the brain include increased neuroplasticity, blood flow, growth of new brain cells, and mood benefits that can
Gst simplified vikram sankhala
GST aims to simplify India's indirect tax system by introducing one indirect tax to replace multiple taxes. It faces challenges in balancing revenue sharing between the central and state governments. The new system introduces IGST to address inter-state transactions. It reduces compliance burdens by providing a single registration and return filing point. However, input tax credit claims are only allowed if matching invoices show the seller paid taxes, which may require contract modifications. Dual empowerment of central and state authorities to audit returns could lead to conflicting assessments.
Paper -future_of_finance_function
The document discusses the evolution of the finance function from the 1960s to present and future. It describes how the finance function has transformed from a focus on "creative accounting" and scorekeeping to prioritizing compliance, efficiency, decision support, and becoming a business partner. The future of finance is outlined as providing predictive insights into performance, growth, and risk to help drive business decisions as a true strategic partner. Finance is utilizing new technologies and analytical skills to integrate diverse data sources and provide real-time insights beyond just financial data.
Transfer pricing 2013 sept 20th by vikram singh sankhala
Transfer pricing 2013 sept 20th by vikram singh sankhalaVikram Sankhala IIT, IIM, Ex IRS, FRM, Fin.Engr
Transfer pricing provisions in India revolve around international transactions between associated enterprises. The key concepts are international transaction, associated enterprise, and arm's length price. Tax authorities require documentation to establish that transfer prices are at arm's length. Non-compliance can result in income adjustments and penalties. Safe harbour rules provide certain transactions predefined arm's length pricing.An Introduction to Risk - by Vikram Sankhala
This document provides an introduction to risk and discusses key concepts related to predicting and modeling risk. It defines risk as a set of measured uncertainties where some outcomes could result in significant loss. It discusses factors that can increase the risk of a heart attack and challenges in predicting who specifically will have one. The document also introduces concepts like stochastic processes, Markov processes, Monte Carlo simulation, and the random walk hypothesis which are used to model and predict risk. It notes the components that contributed to past financial crises and how simulation methods can be used to analyze risk. The overall objective of risk management is to take care of uncertainty and allow for better planning and more secure outcomes.
Transfer Pricing Vikram Sankhala
Transfer pricing regulations aim to ensure multinational companies pay appropriate taxes based on real economic activity in each country. When tax rates differ between countries where a multinational operates, there is an incentive to shift profits to low tax jurisdictions. To prevent tax losses, many countries have introduced transfer pricing laws governing prices on cross-border transactions between related entities. The arm's length principle requires related party transactions be priced as if they occurred between unrelated parties. Various transfer pricing methods, like comparable uncontrolled price method and cost plus method, can be used to determine the arm's length price applicable to related party deals.
Tax issues in mergers and acquisitions
This document discusses various tax issues that arise in mergers and acquisitions under Indian tax law. It covers topics like the meaning of amalgamation, capital gains tax exemptions for amalgamations, treatment of losses and depreciation for the amalgamated company, international tax issues like transfer pricing and thin capitalization. It provides an overview of the key domestic tax provisions around amalgamations, demergers and slump sales. It also gives a brief introduction to concepts of international taxation like offshore financial centers and their implications.
LTCM Case
Long Term Capital Management (LTCM) was a hedge fund founded in 1994 by John Meriwether that utilized quantitative models and leverage to profit from convergence trades. While initially successful, LTCM lost billions in 1998 during the Russian financial crisis as markets became volatile and liquidity dried up. To prevent systemic risk, the Federal Reserve orchestrated an emergency bailout. The crisis showed that highly leveraged positions are vulnerable to shifts in market liquidity and correlations between assets. Key lessons include incorporating liquidity as a risk factor, stress testing models, and relying more on judgment than purely quantitative analysis.
Asset Liability Management
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Global financial markets
This document provides an overview of global financial markets and their terminology. It discusses how trading occurs both on formal exchanges and over-the-counter markets. Financial exchanges provide price information, counterparty protection, and facilitate trading. OTC markets allow customization but lack exchange protections. Major debt, foreign exchange, and derivatives markets operate via OTC arrangements and inter-dealer brokers.
Tax presentation business income
This document summarizes key provisions around deductions allowed under business and professional income in the Income Tax Act. It discusses sections related to deductible expenses like depreciation, preliminary expenses, scientific research, etc. It also covers inadmissible expenses and special provisions for certain industries. Specific deductions are outlined for tea/coffee development funds, site restoration funds, voluntary retirement schemes, and insurance premiums. The document categorizes the various deduction sections and provides explanations of select concepts like block of assets and mandatory claiming of depreciation.
Tax planning for salaried individuals
This document discusses tax planning strategies for salaried individuals, dividing them into salary restructuring and investing in tax-saving devices. For salary restructuring, it recommends structuring salary to include tax-exempt allowances like housing, uniforms, education, etc. It also discusses commuting pension and transferring provident funds. For tax-saving investments, it lists options under sections 80C, 80D, 80E, 80G, etc and explains how to claim deductions and maximize tax savings within the specified limits.
Tax presentation salaries part 2
The document discusses various aspects of taxation related to salaries in India such as taxation of retrenchment compensation, provident funds, perquisites, and more.
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Tax presentation salaries part i
The document discusses the taxation of salaries under the Indian Income Tax Act of 1961. It defines what constitutes a salary and examines the relationship between employers and employees. It also outlines what qualifies as taxable salary components according to the Act, including basic salary, allowances, bonuses, retirement benefits, and perquisites.
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Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
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Equivariant neural networks and representation theory
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
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Non linear dynamical systems
- 1. NON LINEAR DYNAMICAL SYSTEMS VIKRAM SINGH SANKHALA
- 2. ISOLATED SYSTEM • Zero interaction with environment. • In Real World it is difficult to isolate a system from its Environment
- 3. NON LINEAR SYSTEMS • Multiple Inputs • Feedback Loops • Error grow Exponentially • Sensitivity to Initial Conditions
- 4. DISTRIBUTED SYSTEMS • Multiple Interacting Non Linear Dynamic Systems as Components
- 5. MODELLING NON LINEAR DYNAMICAL SYSTEMS • Stochastic noise-driven linear and nonlinear dynamical systems. • Another approach involves a state space where time series observations are transformed to the phase space vectors. They model the dynamics of a system by modeling the dynamics of the corresponding points in the phase space using a Mapping Function • The Mapping Function can be used for Prediction of future states.
- 6. DIMENSION REDUCTION • Principal Components Analysis – Linear Method • Non Linear Techniques are also there
- 7. ALGORITHMIC METHODS • As soon as you introduce self-loops in your model structure, you introduce time, and therefore the system becomes dynamical. • In many statistical models, we don't have a closed form solution for inference on particular variables, so we must use iterative/algorithmic methods to approximate / sample values. • Neural Networks play an important role for modelling Dynamic non linear systems.
- 8. ARTIFICIAL NEURAL NETWORKS • Consist of Connected local processing elements (neurons) • These accept weighted inputs from other such elements • They use these weighted inputs to give a single output
- 9. FREEMAN 1991 • Artificial neural systems were designed to capture some of the useful brain functions by modeling the features of the brain. • Chaos "may be the chief property that makes the brain different from an artificial- intelligence machine“.
- 10. CHAOS • Chaos is statistically indistinguishable from randomness, and yet it is deterministic and not random at all. • A chaotic system will produce the same results if given the same inputs • But you can not predict in what way the system's behavior will change for any change in the input to that system • It is random appearing, and yet has a large degree of underlying order.
- 11. BUTTERFLY EFFECT • Affects Initial Conditions • Initial Condition inaccuracy grows exponentially. • We get extra ordinary and Counter Intuitive Results
- 12. CHAOS ENGINEERING • How Emergent behavior from Component Interactions can cause the system to devove into Chaotic state, • Controlled Experiments on Distributed Systems by introducing failure.