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- 3-CNF-SAT
- Abstrakte problemer
- Aktivitetsproblemet
- Algorithms
- Algoritme - Algorithms
- Antiparallelle kanter
- Asymptotic Notation
- Balansert binærtre
- Banesammenligning - Path Compression
- Bellman-Ford
- Beslutningsproblem
- Bevis - Masterteoremet
- BFS-LABELING
- Binær tre
- Binære søketrær
- Binærrelasjon
- Bipartitt graf
- Bredde-først søk (BFS)
- Bucket Sort
- Build-Max-Heap
- Change base logarithm
- CIRCUIT-SAT
- CLIQUE
- Co-NP definert ved formelle språk
- CONNECTED-COMPONENTS
- Dag-Shortest-Paths
- Datastruktur
- Del 3 - Data Structures
- Del 5 - Advanced Data Structures
- Del 6 - Graph Algorithms
- Delsekvens (Subsequence)
- Dens graf - Dense Graph
- Dijkstras algoritme
- Disjunkt-mengde skoger
- Disjunkte mengder
- Divisjonsmetoden - Division Method
- Dybde-først søk (DFS)
- Dynamisk programmering
- Edmonds-Karps algoritme
- Enkel sti
- Enkoding
- EXTENDED-SHORTEST-PATHS
- FASTER-APSP
- FIND-SET
- Flere kilder eller flere sluk
- Floyd-Warshalls algoritme
- Flyt
- Flytnett
- Flytverdi
- Ford-Fulkerson
- Formelle språk
- Forøkende sti - Augmenting Path
- Fritt trær
- Fullt binærtre
- Gale-Shapley
- GENERIC-MST
- Glissen graf - Sparse Graph
- Grådige algoritmer
- Grådighetsegenskapen
- Graf
- Grafrepresentasjon
- Hamiltonian cycle problemet (HAM-CYCLE)
- Hashtabell
- Hauger
- Hauger - Heaps
- Heap-Extract-Max
- Heap-Increase-Key
- Heap-Max
- Heapsort
- Heltallsteoremet
- Hersk og splitt - Divide-and-Conquer
- Heuristic programming
- Heuristikk for å forbedre kjøretid
- Huffmankoding
- Hvordan bevise NPC generelt
- Hvordan lage en hashfunksjon
- Hvordan unngå kollisjoner - Collision Resolution Technique
- In-Place Algorithm
- Independent uniform hash function
- INITIALIZE-SINGLE-SOURCE
- Inorder Tree Walk
- Insertion Sort
- Iteration Method
- Johnsons algoritme
- Kant
- Kantklassifisering
- Kapasitet
- Kapittel 1 - The Role of Algorithms in Computing
- Kapittel 2 - Getting Started
- Kapittel 3 - Characterizing Running Times
- Kapittel 4 - Divide-and-Conquer
- Kapittel 6 - Heapsort
- Kapittel 7 - Quicksort
- Kapittel 8 - Sorting in Linear Time
- Kapittel 10 - Elementary Data Structures
- Kapittel 11 - Hash Tables
- Kapittel 12 - Binary Search Trees
- Kapittel 15 - Greedy Algorithms
- Kapittel 16 - Amortized Analysis
- Kapittel 19 - Data Structures for Disjoint Sets
- Kapittel 20 - Elementary Graph Algorithms
- Kapittel 21 - Minimum Spanning Trees
- Kapittel 22 - Single-Source Shortest Paths
- Kapittel 23 - All-Pairs Shortest Paths
- Kapittel 24 - Maximum Flow
- Kapittel 25 - Matchings in Bipartite Graphs
- Kjeding - Chaining
- Kø - Queue
- Kolisjon - Collision
- Kompleksitetsklassene
- Korteste vei fra alle til alle
- Korteste vei fra en til alle
- Left
- Lenket liste - Linked List
- Lett kant
- LINK
- LIST-PREPEND
- LIST-SEARCH
- MAKE-SET
- Maksimal flyt - Maximum flow
- Maksimum bipartitt matching
- Master-theorem
- Max-flow min-cut Teoremet
- Max-Heap-Extract-Max
- Max-Heap-Increase-Key
- Max-Heap-Insert
- Max-Heap-Maximum
- max-heap-property
- Max-Heapify
- max-heaps
- max-priority queues
- Merge
- Merge-Sort
- Metoder for å finne minimale spenntrær
- min-heap property
- min-heaps
- Minimale spenntrær
- Minimalt snitt og heltallsteoremet
- MST-KRUSKAL
- MST-PRIM
- Multiplikasjon,shift metoden - Multiply-shift method
- Multiplikasjonsmetoden - Multiplication Method
- Nabolister
- Nabomatrise
- Nabomatriser
- Naiv Algoritme
- Nettoflyt
- NP definert ved formelle språk
- NP problem
- NP-harde problemer (NPH)
- NP-komplett problem (NPC)
- NP-komplett ved formelle språk
- NP-Kompletthet
- NPC problemer
- Optimal Delstruktur
- Optimeringsproblemer
- Optimum
- Overlappende Delinstanser
- Oversikt AlgDat
- P problem
- P=NP
- Parent
- Partition
- Pensumoversikt AlgDat
- Perfekt binærtre
- Polynomisk tid
- PRINT-ALL-PAIRS-SHORTEST-PATH
- Prioritetskøer - Priority queues
- Problemer og Algoritmer
- Quicksort
- Radix-Sort
- Random-access machine (RAM)
- Randomized Partition
- Randomized Quicksort
- Randomized Select
- Rang
- Recurrence Equations
- Recursion tree
- Reduksjon ved formelle språk
- Redusibilitet
- Regularity Condition
- RELAX
- Representant-node
- Restnett - Residual Network
- RIGHT
- Rotfast tre
- Rotfaste trestrukturer
- Ryggsekkproblemet
- SAME-COMPOMENT
- Sammenligningsalgoritme
- SAT
- Sentinels
- SLOW-APSP
- Sorteringsgrensa
- Spenntrær
- Spenntrær, kruskal og prim
- Språkteori for NPC problemer
- Stakk - Stack
- Stirlings approximation
- SUBSET-SUM
- Substitution Method
- Substring
- Superpolynomisk tid
- Topologisk sortering
- Trær
- Transitive Closure
- Traveling Salesman Problem (TSP)
- Traversering av grafer
- Tree-Insert
- Tree-Search
- Trygg kant
- UNION
- Union etter rang - Union By Rank
- Untitled
- Urettet trær
- Vektede grafer
- Verifikasjonsalgoritme
- VERTEX-COVER
- Aliasing
- Aliasing - Folding
- Autocorrelation
- Autocorrelation estimators
- Autoregressive (AR) Process
- Autoregressive, Moving Average (ARMA) process
- Bandlimited Signal
- Chapter 5 - Frequency-Domain Analysis of LTI Systems
- Chapter 12 - Linear Prediction and Optimum Linear Filters
- Circular Convolution
- Crosscorrelation
- Decimation
- Design of Digital Filters - FIR, IIR
- DFT - Discrete Fourier Transform
- DFT - Discrete Fourier Transform for Filtering and Frequency Analysis
- Direct form 1 - DF1
- Direct form 2 - DF2
- Discrete Random Signals
- DTFT - Discrete Time Fourier Transform
- Energy Density Spectrum
- Energy spectral density
- Ensemble Average
- Ergodic process
- Estimation Basics and Periodogram
- FFT- Fast Fourier Transform
- Filter Structures
- Finite Geometric Series
- Finite-Precision Effects
- Forward Linear Prediction
- Frequency-Domain Analysis of LTI Systems
- Gauss-Markov Process
- Geometric series
- Input-output correlations
- Interpolation
- Inverse Z-transform and Residues
- Linear Phase
- Linear Prediction
- Minimum-Phase
- Modeling of Stochastic Processes
- Moving Average (MA) process
- Multirate signal processing
- Noise-Whitening Filter
- Nyquist Sampling Theorem
- Power Density Spectrum (PDS)
- Quantization in digital filters
- Radix-2 FFT
- Rate
- Region of Convergence
- Relationship between DTFT and DFT
- Sampling and Reconstruction Of Signals
- Sampling Theorem
- Signals
- Stochastic Processes
- Stochastic signal
- Time Domain Aliasing
- Untitled
- Wagon Wheel Effect
- Wide-sense stationary process
- Wiener Filter
- Wold representation
- Yule-Walker equations
- Yule-Walker Method for AR Model Parameters
- Zero Padding
- Addivity
- Algebraic Equivalence
- Algebraic Ricatti Equation
- Asymptotic Stabillity
- Autocovariance
- Band-limited Differentiation
- Basis
- BIBO Stability
- Canonical Decompositions
- Canonical Forms
- Causality
- Cayley Hamilton Theorem
- Certainty Equivalence
- Chapter 1 - Introduction
- Chapter 2 -Mathematical Descriptions of Systems
- Closed-loop Estimator - Luenberger Observer
- Colored Noise
- Colored Noise in Kalman Filter
- Comprime
- Controllability
- Controllability Gramian
- Controllability Index
- Controllability Matrix
- Controllable Canonical Form
- Controllable Form
- Conveyor Belt Case Study
- Covariance Matrix
- Covariance Matrix of the Estimation Error
- Deterministic process
- Diagonal Form
- Discrete Time Covariance Matrix of the Estimation Error
- Discrete Time Kalman Filter
- Discrete Time Kalman Gain Matrix
- Discretization
- Dual System
- Duality
- Equivalent Representations of Systems and Matrices
- Equivalent Systems
- Estimate Update Law
- Estimation Error
- Euler Discretization
- Exact discretization
- Exponential Stability
- Functions of a Square Matrix
- Functions of Finite Polynomials
- Homogeneity
- Improper Transfer Function
- Integral Effect
- Internal Stability
- Jordan Block
- Jordan Form
- Kalman Filter
- Kalman Filter for Time Varying Models
- Kalman Filter in Continuous Time
- Kalman Gain
- Leading Principle Minors
- Lecture 2 - Equivalent representations, canonical forms, functions of square matrices
- Lecture 3 - Discretization, Controllability, State feedback
- Lecture 4 - State feedback, Optimal control
- Lecture 5 - Realizations, Observability
- Lecture 6 - State estimation and the separation principle
- Lecture 7 - Stability
- Lecture 8 - Canonical Decompositions and Minimal Realizations
- Lecture 9 - Random Processes
- Lecture 10 - Random State Space Systems
- Lecture 11 and 12 - The Kalman Filter
- Linear System
- LinSys; Linear Quadratic Regulator - LQR
- LQR and Kalman Filter Duality
- Lyapunov Test for Controllability
- Lyapunov Test for Stability
- Lyapunov Theorem
- Marginal Stability
- Matrix rules and tricks
- Measurement Equation Inversion
- Memoryless system
- Minimal Realization
- Minimal realizations
- Modal Form
- Multi-input Controllability
- Noise Supression
- Nonsingular matrix
- Null Space
- Nullity
- Observability
- Observability Gramian
- Observability Matrix
- Open-loop Estimator
- Output feedback controller
- Overview LinSys
- Popov-Belevitch-Hautus Test
- Positive-Definite Matrix
- Proper
- Proper Transfer Function
- Random processes
- Random State Space Systems
- Real constant matrix
- Realizations
- Reference Feed-Forward
- Separation Principle
- Similarity Transform
- Stability
- Stability in Discrete Time
- Stabilizability
- State Estimation
- State Feedback, and Optimal Control
- State Space Representation
- State-feedback
- Stationary Random Processes
- Strictly Proper Transfer Functions
- Superposition
- Symmetric Matrix
- Time Invariance
- Transformation Matrix
- TTK4115-Pensum Oversikt
- Zero-state Equivalence
- Balansen
- Bedriftssimulator
- Beslutningstrær
- Beta - enkeltaksjers bidrag til porteføljerisiko
- Bruk av kapitalverdimodellen
- Budsjettering
- Capital Asset Pricing Model - CAPM SLASH Kapitalverdimodellen - KVM
- Debet og kredit
- Dekningsbidrag
- Dekningsgrad
- Diskonteringsrente
- Dobbel bokføring
- Dødvektstap
- Egenkapitalrentabilitet R_EK
- Ekstraordinære kostnader
- Erfaringsgoder
- Etterspørsel (Q(P))
- Etterspørselselastisitet (ε)
- Finansieringsanalyse-gjeldsgrad og soliditet
- Finansregnskapet
- Følsomhetsanalyse
- Forelesningsplan
- Fortjeneste
- Frikonkurranse
- Giring - bruk av lån til å øke egenkapitalrentabiliteten
- Gjeldsgrad
- Gjennomsnittsinntekt (AR)
- Gjennomsnittskostnad (AC)
- Gjennomsnittsproduktiviteten til arbeid (GPL)
- Grensen for diversifisering
- Grunnleggende regnskapsbegreper
- Grunnleggends regnskapsanalyse av finansregnskapet
- Historisk risiko og avkastning
- Indirekte kostnader
- Inntakskost (Direkte kostnad)
- Inntekt og marginalinntekt (TR, MR)
- Internregnskapet
- Internrenteberegning og bruk av internrenten
- Investeringer
- Isokostnadskurven
- Isokvanter
- Kalkyle etter bidragsmetoden
- Kalkyle etter selvkostmetoden
- Kalkyler
- Kapittel 6 - Organisasjonsstruktur
- Kapittel 13 - Mikroøkonomi og markedsformer
- Kapittel 14 - Regnskapsanalyse og økonomistyring
- Kapittel 15 - Investeringsanalyse
- Konsumentoverskudd KO
- Kortsiktige produksjonsfunksjoner
- Kostnad
- Kostnader (TC, VC, FC, AC)
- Kostnadsbegreper
- Kostnadsbudsjett
- Kostnadsstruktur
- Kredittrisiko
- Læringskurveeffekt
- Langsiktige produksjonsfunksjoner
- Likviditetsanalyse
- Likviditetsbudsjett
- Likviditetsgrad 1
- Likviditetsgrad 2
- Lønnsomhetsanalyse-total-og egenkapitalrentabilitet
- Loven om avtakende marginalprodukt
- Mål på risiko
- Marginalkostnad (MC)
- Marginalproduktiviteten til arbeid (MPL)
- Markeder med frikonkurranse
- Markeder med to eller få produsenter (duopol,oligopol)
- Markedsportefølje
- Mikroøkonomisk teori som modellapparat
- Modigliani og Millers andre proposisjon - MnM II
- Modigliani og Millers første proposisjon - MnM I
- Monopol og dødvektstap
- Monopol, duopol og oligo poler
- Monte Carlo simulering
- Nash-likevekt
- Naturlige monopoler
- Nåverdi NV
- Nåverdiberegninger
- Negative skalaeffekter - Skalaulemper
- Nettonåverdi NNV
- Nullpunkt
- Nullpunktsanalyser
- Pareto-optimal
- Pekuniære skalaeffekter
- Portefølje
- Porteføljerisiko
- Positive skalaeffekter
- Pristilpassere
- Produsentoverskudd PO
- Profitt (Ⲡ) og analyse av profitt
- Profitt og analyse av profitt
- Reelle skalaeffekter
- Rentedekningsgrad
- Resultatbudsjett
- Resultatregnskapet
- Risiko og avkastning
- Risikoanalyse
- Samfunnsøkonomisk dødvektstap
- Samfunnsøkonomisk lønnsomhet SO
- Sammenheng etterspørselselastisitet og marginalinntekt
- Scenarioanalyse
- Selskapets kapitalkostnad og verdipapirmarkedslinjen
- Selvkost
- Selvkostkalkyle i handelsbedrifter
- Sharpe Ratio
- Sikkerhetsmargin
- Skalaavkastning
- Søkegoder
- Soliditetsgrad
- T-konto
- Teknologi, substitusjon og isokvanter
- Tidsverdi
- Tilbud og markedslikevekt
- Tillitsgoder
- Totalrentabilitet R_TK
- Ulike markedesformer
- Utbetaling
- Utgift
- Leseplan - 5. Semester
- Asymptotic Properties of the MLE
- Bayes Decision Rule
- Bayes Risk
- Bayes Theorem
- Bayes' Law
- Bayesian Detection
- Bayesian Estimation
- Bayesian Estimators
- Bayesian MSE Estimators
- Best Linear Unbiased Estimator (BLUE)
- Binary Hypothesis
- Central Moments of a Random Variable
- Classical Estimation
- Classifiers based on Bayes Decision Theory
- Clustering
- Confusion Matrix for Hypothesis Testing
- Cramer-Rao Lower Bound
- Decision Regions
- Density Estimation
- Detector
- Efficient Estimator
- Estimation Theory
- Fisher Matrix
- General Bayesian Estimators
- General Linear Model
- Independent and Identically Distributed Random Variables
- Invariance Property of the MLE
- K-means Clustering
- Lecture 1 - Course Description
- Lecture 2 - Review of Probability Theory, Random Variables and Stochastic Processes
- Lecture 3 - Minimum-Variance Unbiased Estimation
- Lecture 9 - Hypothesis Testing
- Lecture 10 - Neyman-Pearson and Bayesian Detectors
- Lecture 11&12 - Matched Filter and Replica Correlator
- Lecture 14&15 - Classification and Classification Systems
- Lectures Estimering
- Likelihood Function
- Likelihood-Ratio Test
- Linear Classifier
- Linear Discriminant Function
- Linear Mapping
- Linear Model
- Linear Model with Non-White Noise
- Linear Separable Problem
- Mean Square Error
- Minimum Mean Square Error
- Minimum Probability of Error
- Minimum Variance Unbiased Estimator
- Moments of a Random Variable
- Multiple-Hypotheses Testing
- Neyman-Pearson Theorem
- Noise Covariance Matrix
- Non-Separable Problem
- Nonlinear Separable Problem
- Nonparametric Techniques
- Observation Space
- On-off Keyed Communication
- Parzen-Window
- Power of Test
- Receiver Operating Characteristics
- Reciever
- Reinforcement Learning
- Semi-Supervised Learning
- Sigmoid
- Size of Test
- Statistical Independence
- Sufficient Statistic
- Supervised Learning
- The Best Linear Unbiased Estimator
- The Estimator for the Linear Model
- The Maximum Likelihood Estimator
- The Maximum-a-posteriori Estimator
- The Minimum Variance Criterion
- TTT4275 - Estimering, deteksjon og klassifisering
- Unbiased Estimator
- Unsupervised Learning
- Untitled
- With Regards To
- Acceleration Form
- Accuracy of the Forward (Explicit) Euler Method
- Angle Axis Representation
- Angular Acceleration
- Angular Momentum
- Angular Velocities
- Basic 1-port Elements
- Basic 2-port Elements
- Basic Elements
- Basic Hydraulic Components
- Butcher Tableau
- Causal Stroke
- Cheat sheet for exam
- Composite Rotation Transformation
- Configuration Space
- Consistency Condition
- Constrained Lagrange
- Course Recap
- Differential Algebraic Equations
- Differential Index
- Effort
- Energy Flow Direction
- Euler Angles
- Euler Half-Step
- Euler-Lagrange Equation
- Flow
- From a Vector to a Skew Symmetric Matrix
- Generalized Coordinates
- Generalized Forces
- Generalized Momentum Force
- Global Error
- Hydraulic system modelling procedure
- Kinematics Module
- Kinetic Energy
- Kinetics in Linear Motion
- Kinetics in Rotation
- Lagrange Equation
- Lagrange Mechanics
- Lecture 01 - Introduction
- Lecture 02 - Modelling and Simulation
- Lecture 03 - Kinematics 1
- Lecture 04 - Kinematics 2
- Lecture 05 - Kinematics 3
- Lecture 06 - Kinematics 4
- Lecture 07&08 - Rigid Body Dynamics 1&2
- Lecture 09&10 - Rigid Body Dynamics 3&4
- Lecture 11&12 - Rigid Body Dynamics 5&6
- Lecture 13&14 - System Dynamics
- Lecture 15 - Basic System Modelling 3
- Lecture 16 - Basic System Modelling 4
- Lecture 17&18 - Basic System Modelling 5&6
- Lectures ModSim
- Linear Acceleration
- Linear Momentum
- Linear Velocity
- Linear Velocity of a Point That Is Fixed Within a Rotating Reference Frame
- Mid-Point Method
- New Lagrangian
- Newton-Euler Equations of motion
- Notation ModSim
- Numerical Simulation
- Ordinary Differential Equation
- Parallel Axis Theorem
- Potential Energy
- Power Bonds
- Power Variables and Energy Variables
- Principal Rotation Matrix
- Procedure for Modelling Electrical Systems
- Procedure for Modelling Mechanical Systems
- Properties of Rotation Transform Matrices
- Punctual Mass
- Recap Rigid Body Dynamics
- Reference Frame
- Reynolds Number
- Rotation Matrix
- Rotation Transformation
- Skew-Symmetric Cross Product Matrix Formula
- Skew-Symmetric Matrix
- Stability of the Forward Euler Method
- State Space Formulations
- Subsystems
- Tetrahedron of State
- Transformer Element
- TTK4130 - Modellering og simulering
- Exercise 0 - Matrix Calculus
- Exercise 1 - The KKT Conditions
- Exercise 2 - LP and KKT Conditions
- Exercise 3 - LP, QP, and KKT Conditions
- Exercise 4 - Quadratic Programming
- Exercise 5 - Open-Loop Optimal Control and MPC
- Exercise 6 - MPC and LQR
- Exercise 7 - Riccati Equation and State Estimation
- Exercise 8 - Unconstrained Optimization
- ∞-norm
- 1-norm
- 2-norm
- Active Set
- Active-Set Method for Convex QP
- Basic Feasible Point (BFP)
- BFGS update formula
- Bias Update
- Common Vector Norms (p-norms)
- Condition Number
- Constrained Problem
- Constraint Qualification
- Convex Objective Function
- Convex Optimization Problem
- Critical Cone
- Degeneracy
- Descent Directions
- Detectability
- Duality for Nonlinear Programming
- Dynamic Optimization
- Equality-Constrained Quadratic Programs
- Example of Simplex Method
- Feasible
- Feasible Set
- Fundamental Theorem of Linear Algebra
- General Algorithm for Solving Unconstrained Optimization
- General Dynamic Optimization Problem
- General Optimization Problem
- Gradient
- Gradient With Respect to a Variable
- Hessian
- Horizon
- Ill conditioned Matrix
- Inequality Constraint
- Infimum
- Jacobian
- KKT (Karush–Kuhn–Tucker) Conditions
- KKT Matrix for Equality-Constrained QPs
- Lagrangian
- Lecture 1 - Optimization, What and Why?
- Lecture 2 - Optimality Conditions
- Lecture 3 - Optimality conditions, constraint qualifications, 2nd order optimality conditions
- Lecture 4&5 - Linear Programming (LP)
- Lecture 6&7 - Quadratic Programming
- Lecture 8 - Open-Loop Dynamic Optimization
- Lecture 9 - Linear Quadratic Control
- Lecture 10 - Model Predictive Control
- Lecture 11 - Practical use of MPC
- Lecture 12 - Summing up MPC and LQ
- Lecture 13 - Unconstrained Optimization
- Lecture 15 - Quasi-Newton
- Lecture 16 - Calculating Derivatives and Derivative-Free Optimization
- Line Search Methods
- Linear Independence Constraint Qualification
- Linear Programming
- Lipschitz Continuity
- LU Decomposition
- Matrix Factorization
- Matrix Inversion Lemma
- Mean Value Theorem
- Necessary Condition
- Newton Direction
- Newton's Method for Nonlinear Equations
- Nominal Stability
- Nonlinear Equations
- One step of Simplex-Algorithm
- Optimality Conditions
- Optimization
- Positive-Semidefinite Matrix
- Properties of Linear Programming Problems
- Quadratic Programming Problem on Standard Form
- Quasi-Dynamic Optimization
- Quasi-Newton
- Range Space
- Robust Stability
- Rosenbrock Function
- s
- Scaling
- Secant Equation
- Second-Order Necessary Conditions (SONC)
- Second-Order Sufficient Condition (SOSC)
- Sensitivity
- Sensitivity Analysis
- Sequential quadratic programming
- Simplex Method
- Slack Variable
- Standard LP
- Static Optimization
- Steady State
- Steepest Descent
- Step Length
- Strong Duality
- Sufficient Condition
- Taylors Theorem
- Termination Criteria
- The Dual LP Problem
- The Feasibility Problem
- The Set of Linearized Feasible Directions
- Transforming a Linear Programming Problem Into Standard Form
- Types of Constrained Optimization Problems
- Weak Duality
- Well-Conditioned Matrix
- Wolfe Condition
- Code Quality Trial Exam
- Conditional Critical Region
- Critical Region
- Fixed-Priority Scheduling
- Introducing Shared Variable Synchronization Trial Exam
- Monitors
- Mutual Exclusion
- Overview Exam Sanntid
- Producer-Consumer
- Response Time Analysis for FPS
- Scheduling
- Scheduling Test
- Shared Variable Synchronization Trial Exam
- Shared Variable-Based Synchronization and Communication
- Static and Dynamic Scheduling Scheme
- Task-based Scheduling
- The Cyclic Executive Approach
- Utilization-Based Schedulability Test for FPS
- V2023
- Acceptance Test
- ACID properties
- Atomic Actions
- Atomic Actions, Concurrent Tasks and Reliability
- Atomic Operation
- Atomic Transactions
- Atomicity
- Backward Error Recovery
- Basic Fault Tolerance
- Checkpoint-Restart
- Concurrent Events
- Consistency
- Context Switch
- Cooperative Scheduling
- Coordinator
- Domino Effect
- Durability
- Dynamic Redundancy
- Encapsulation
- Execution Model
- Failure Modes
- Fault Model and Software Fault Masking
- Fault Prevention
- Fault Tolerance
- Forward Error Recovery
- How Sleep Works
- Intelligent Design
- Isolation
- Lecture 2&3 - Code Quality
- Lectures sanntid
- Lightswitch
- Maintainable System
- Module
- N-Version Programming
- Preemptive Scheduling
- Process Pair
- pthread
- pthread_create()
- Race Conditions
- Redundancy
- Reliable Calculations
- Reliable Communication
- Reliable Data Storage
- Scheduler
- Semaphores
- Shared Variable Synchronization
- Sockets
- Source D-Compiler
- Starting a Thread
- Synchronization
- TCP (Transmission Control Protocol)
- The Resumption Model of Asynchronous Notification Handling
- Thread
- Thread Swapping
- Transactions
- TTK4145 - Sanntidsprogrammering
- Turnstile
- Two-Phase Atomic Actions
- UDP (User Datagram Protocol)
- Week 9 - Atomic Actions, Leaving backward error recovery
- Timeplan 6.semester
- 2D manifold
- 3D Rasterization Pipeline
- Affine Combination
- Affine Transformation
- Back-Face Culling
- Bidirectional Reflectance Distribution Function
- Catmull's Algorithm
- Center of Projection
- CG Anti-Aliasing
- CIE XYZ Color Model
- Clipping
- Cohen-Sutherland Algorithm
- Color Model
- Convex Affine Combination
- Erosion
- Eye Coordinate System
- Finite Differences
- Frustum Culling
- Graphics Pipeline
- Greiner-Hormann Algorithm
- Grid Traversal
- Hidden Surface Elimination
- Illumination Model
- Inner Product
- Liang-Barsky Algorithm
- Morphological Image Processing
- Normalized Device Coordinates
- Occlusion Culling
- Oversikt Gruvis
- Parallel Projection
- Perspective Projection
- Phong Illimunation Model
- Primitives
- Projection
- Rasterization
- Region Growing
- RGB Color Model
- Scene Managment
- Scene-Graphs
- Sutherland-Hodgman Algorithm
- TDT4195 - Grunnleggende visuell databehandling
- Transformations
- Vertex Array Object
- Vertex Attribute Pointer
- Vertex Attributes
- Z-Buffer Algorithm
- Attitude Representations
- Axioms of Probability
- Bayesian Networks
- Belief Propagation
- Chapman - Kolmogorov Equation
- Chapter 2 - Foundations of Probability Theory
- Characteristic Function
- Chi Squared Distribution
- Clutter
- Dead Reckoning
- Fast-SLAM
- From the Kalman filter to stochastic processes
- Gamma Distribution
- Gamma Function
- Gauss-Newton
- Gaussian Mixtures
- Generating Functions
- Hybrid Chapman - Kolmogorov
- Information Form
- Integrated Probabilistic Data Association
- Interacting Multiple Models
- Joint Probabilistic Data Association
- Joseph Form
- Markov Random Fields
- Moment-Generating Function
- Multi Target Tracking
- Multivariate Gaussian
- Normalized Estimation Error Squared
- Normalized Innovations Squared
- Particle Filter
- Poisson Distribution
- Poisson Point Process
- Probabilistic Data Association Filter
- Probability-Generating Function
- Quaternions
- Rao-Blackwellization
- Sensor - Kalman Filter
- Simultaneous Localization and Mapping
- Single-Target Assumption
- Single-Target Tracking
- The Bayes Tree
- The Error-State Kalman Filter
- The Hybrid State Concept
- The Product Identity
- Total Probability Theorem
- Transformation of Random Variable
- TTK4250 - Sensorfusjon
- White Gaussian Noise
- Wiener Process
- Timeplan 7. Semester
- README
- Annotating Data
- Building Open-CV with Cuda jetsson
- Clang
- Debugger with ROS2 and C++
- Enable Scrolling in tmux
- Fix obsidian git for ipad
- Forward SSH key over SSH
- Git Large File Storage
- Idun HPC
- Image Viewer ROS2
- Language server C++ (ROS2)
- Open Neural Network Exchange
- Orin-NX
- Profiler
- Prompts
- pull submodules
- ROS 2
- ROS2 Developer guide
- Setting up ROS2 project
- shared object
- Show Interface ROS2
- Slurm
- ssh-agent forwarding
- YOLO in C++
- YOLOv8
- README
Heap-Max