'Continuous curve' diaporamas de présentation

spirals

spirals. A spiral winds in a continuous curve round a point. Some spirals are man made. Others are found in natural things such as plants and animals. Spirals in Circles. This type of spiral is called an Archimedean spiral after the Greek mathematician Archimedes.

1.49k views • 114 slides

Generative Models for Image Understanding

Generative Models for Image Understanding. Nebojsa Jojic and Thomas Huang Beckman Institute and ECE Dept. University of Illinois. Problem: Summarization of High Dimensional Data. Pattern Analysis: For several classes c=1,..,C of the data, define probability distribution functions p(x| c)

643 views • 56 slides

Calculus

Math Review with Matlab:. Calculus. Differentiation. S. Awad, Ph.D. M. Corless, M.S.E.E. E.C.E. Department University of Michigan-Dearborn. Differentiation. General Derivatives Diff Command Differentiation Example Product Rule Example Chain Rule Example Partial Differentiation

967 views • 32 slides

Warm Up May 20 th

Warm Up May 20 th. Please pick up the 11-2 Enrichment sheet from the cart and get started (both sides). Tougher Probability. Carson is not having much luck lately. His car will only start 80% of the time and his moped will only start 60% of the time.

393 views • 31 slides

Generation of Influence Lines Using Statics

Generation of Influence Lines Using Statics. Objectives of the materials covered: The student should be able use the equations of statics to generate an influence line for reactions, internal shears, and internal moments at any point in a simply supported beam. Generation of influence lines.

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Square Limit by M.C. Escher

Square Limit by M.C. Escher. How are the fish in the middle of the design and the surrounding fish alike? How are they different?. Square Limit by M.C. Escher. Escher used a pattern of squares and triangles to create Square Limit . . These two triangles are similar.

1.08k views • 24 slides

Efficient Pseudo-Random Number Generation for Monte-Carlo Simulations Using GPU

Efficient Pseudo-Random Number Generation for Monte-Carlo Simulations Using GPU. Siddhant Mohanty , Subho Shankar Banerjee , Dushyant Goyal , Ajit Mohanty and Federico Carminat i. Device: NVIDIA GeForce GTX 480. Compute Capability: 2.0(suitable for double precision)

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2.5 CONTINUITY

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How big is my heart??? (Find the area of the enclosed region)

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Polynomial Functions

1.49k views • 10 slides