This is a video of a multi-input touch screen that hopefully will make its way into consumer computer market in time. A standard touch screen allows one input at a time. This allows multiple people to use it and allows for Minority Report like features. Super Cool

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http://www.FreeScienceLectures.com The usual touch screens usually allow just a single touch interaction. This new technology is designed to be usable by both hands or by multiple persons. The uses are endless. You can use it for creating a fantastic video mixing or special effects. Create interactive presentations which can be modified with both hands. Quickly categorize, resize and move images. Draw some pokemons and make them wiggle. Examine 3D figures more easily. Maps and terrains can be examined. Music can be mixed. And it can be used to display some complex mathematical structures as graphs for example. Sure there are many other uses. --- It's Never too Late to Study: http://www.FreeScienceLectures.com --- Notice: This video is copyright by its respectful owners. The website address on the video does not mean anything. ---

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examples of a multi-input interface i set up for my Engineering project. Uses the Wii remote. LCD hardware for debugging purposes

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Here it is a preview of qadt where you can see MultiInput, MultiPlotting with different scales, Zooming, Panning, PDF Printing and other functions in action.

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NaturalPoint's Warren Blyth demonstrates and explains a form of optical tracking technology that is now being used to enhance control in flight, racing, and FPS games and hints at what's coming next. TrackIR.com has more info...

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Glenn Gould discusses his radio documentary 'The Idea of North' -- drawing comparisons to Verdi's Falstaff, fugue writing, and Webern's tone rows -- and plays Webern's piano Variations (Opus 27). With Bruno Monsaingeon. I highly recommend trying out GG's multi-input listening technique next time you are in a restaurant or other such environment -- it's very fun to try to use just one's own ears to turn the various surrounding sounds (multiple conversations, television, etc) into a sort of musical texture.

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Here's the new multi-input mobile from LG, the KF700.

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Petite vidéo Elane Innovation sur le nouveau tableau interactif multi-input Hitachi FX-Duo.

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This is the first video of my own multitouch display that I have built. It is a quick video showing the multi-touch capability, and the beginnings of its abilities. To find out how it works and more, please go to http://nuigroup.com/

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Students and teachers can work together on the Activboard at the same time and classrooms become dynamic arenas for team-based activities, projects, competition, and group work. Imagine the potential of two, three, or more students working together, or teachers working collaboratively with students at the same time. Transform your classroom with new tools that include multiple pens, activity templates, and software provided by Promethean. Reinvent your classroom and capture your students' imagination

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Inverted pendulum. This is a MIMO (multi input multi output system) The equations were linearized about the vertical position of the stick. The controller was designed using the LQR technique. The microcontroller used is the Ti dsp F2812. for more control videos visit : http://control.mem.drexel.edu/student_projects.htm Quanser (TM) Electro-mechanical assembly used for this project. Yo can find their products on this website: http://www.quanser.com/choice.asp

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Multi Input Device ・Normal Controller ・MIDI Interface ・Bluetooth Device

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Multiple Pointing Input System allows concurrent manipulation of 8 pointing devices. The original work was published in 2000. Please visit http://megaui.net/fukuchi/research/index.en.html for the details.

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on linear functions for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution and transfer matrix descriptions. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, gives an overview of the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution and transfer matrix descriptions. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, gives a review of linear algebra for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution and transfer matrix descriptions. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on matrix exponentials, eigenvectors, and diagonalization and their uses in LDS for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on orthonormal sets of vectors and QR factorization for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution and transfer matrix descriptions. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on controllability and state transfer and their uses in modern electrical engineering for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on the applications of SVD, controllability, and state transfer in electrical engineering for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on the least norm solutions of undetermined equations for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution and transfer matrix descriptions. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on the applications of least squares for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution and transfer matrix descriptions. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on regularized least squares and the Gauss-Newton method for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution and transfer matrix descriptions. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on autonomous linear dynamical systems and how they relate to Electrical Engineering for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on the applications of single value decomposition in LDS and electrical engineering, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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