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    Bca Notes

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    100 Note : Question no. one is compulsory. Attempt any three questions from four. 1. (a) For what value of ’k’ the points ( - k + 1‚ 2 k)‚ (k‚ 2 - 2 k) and ( - 4 - k‚ 6 - 2 k) are collinear. (b) Solve the following system of equations by using Matrix Inverse Method. 3x+ 4y+ 7z= 14 2x-y+ 3z= 4 2x + 2y - 3z = 0 (c) Use principle of Mathematical Induction to prove that : 1 ± 1 ± 1x2 2x3 (d) 1 n (n+1) n+1 5 5 5 5 -‚ How many terms of G.P ‚[3 3‚ 3 /3 Add upto 39 + 13 BCS-012 1 P.T.O

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    Terida

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    description‚ the flowchart‚ the file structures‚ and the selected financial data below‚ specify an audit objective (that can be achieved using ACL™) for each management assertion presented in the matrix below. For each audit objective‚ briefly describe the ACL test procedure. As an example‚ the first row in the matrix has been completed for you. Selected Bradmark Financial Data Sales 5‚379‚996.96 Accounts Receivable 4‚752‚257.70 Allowance for Doubtful Accounts (.02 x Sales)

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    False reality vs. real reality what do we know? In Matrix there were several false reality explored in it‚ most were fun but what if it were used to imprison you? The part where they were working in the computer room‚ and Anderson works on the cubicle‚ manning a computer and doing the hacking on the side when Morpheus who was some what interesting in what’s going on around him is it real. It seemed that Thomas like most people‚ is a victim of The matrix a massive intelligence system that has tapped into

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    Computer Linear Algebra

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    change of basis. In most situations‚ people prefer a better image with high resolution‚ sharper‚ more detail‚ etc. Image can be describes as a collection of pixels that have different component depends on the digital signals that digitized as a matrix. These signals came from different energy such as wavelength‚ frequency. Fourier basis manipulate the image by changing the signal in the pixels. Some signals that give a similar coefficient can be eliminated so that the picture become blurrier or

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    Without this generation’s digital trail of YouTube videos‚ Facebook messages‚ emoji-studded texts‚ and reverse-camera confessionals‚ the documentary Twinsters would be a h3very different movie‚ there probably wouldn’t even be a movie. The sisters wrote a book about their experience in 2014‚ Separated@birth‚ and now one of them has made this movie. A real-life story told in “Twinsters”‚ a pair of twins separated at birth found each other and reunited thanks to the Internet. Samantha Futerman and

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    Sudoku game

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    of each column is unique 2. The value of each row is unique 3. The amount per square N * N is a unique internal[-http://www.cs.huji.ac.il] Percepts The Sudoku Game percepts are: 1-The field of Sudoku environment matrix is blank 2-The field of Sudoku environment matrix is not blank 3-The value of each filled row is unique 4-The value of each filled row is not unique 5-The value of each filled column is unique 6-The value of each filled column is not unique 7-The summation per each

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    Adaptive filters

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    Adaptive Filters 1 Adaptive Filters A Tutorial for the Course Computational Intelligence http://www.igi.tugraz.at/lehre/CI Christian Feldbauer‚ Franz Pernkopf‚ and Erhard Rank Signal Processing and Speech Communication Laboratory Inffeldgasse 16c Abstract This tutorial introduces the LMS (least mean squares) and the RLS (recursive least-squares) algorithm for the design of adaptive transversal filters. These algorithms are applied for identification of an unknown system. Usage

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    Question case study

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    activities; matrix structure UD: 12/12/2012 Overview and Objectives: The case examines the organizational and managerial challenges involved in offshoring and internationalizing substantial portions of firms’ organizational activities to foreign countries. Students will need to consider the learning journey Coloplast underwent in this process‚ from managing the reconfiguration to the implementation of a new and complex design. They have to understand the features and challenges of the matrix form

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    Java and Web Technologies

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    www.jntuworld.com www.jwjobs.net NEURAL NETWORKS Ivan F Wilde Mathematics Department King’s College London London‚ WC2R 2LS‚ UK ivan.wilde@kcl.ac.uk www.jntuworld.com www.jntuworld.com www.jwjobs.net Contents 1 Matrix Memory . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2 Adaptive Linear Combiner .................... 21 3 Artificial Neural Networks .................... 35 .......................... 45 5 Multilayer Feedforward Networks

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    Gauss Markov Theorem

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    [pic] the best (minimum variance) linear (linear functions of the [pic]) unbiased estimator of [pic]is given by least squares estimator; that is‚ [pic]is the best linear unbiased estimator (BLUE) of [pic]. Proof: Let [pic]be any [pic]constant matrix and let [pic]; [pic] is a general linear function of [pic]‚ which we shall take as an estimator of [pic]. We must specify the elements of [pic]so that [pic]will be the best unbiased estimator of [pic]. Let [pic] Since [pic] is known‚ we must find

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