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Hidden verification for computational mathematics

Hanne Gottliebsen, Tom Kelsey, Ursula Martin
2005 Journal of symbolic computation  
We present hidden verification as a means to make the power of computational logic available to users of computer algebra systems while shielding them from its complexity.  ...  Hence we are able to support the analysis of differential equations in Maple by direct calls to PVS for: result refinement and verification, discharge of verification conditions, harnesses to ensure more  ...  We thank Mike Dewar of NAG Ltd for his interest and suggestions, James Davenport, Manuel Bronstein for advice on computer algebra, and the members of the PVS mailing list for many swift answers.  ... 
doi:10.1016/j.jsc.2004.12.005 fatcat:lqoooacsufcvnbx5jgsdkk35ke

Delta Ruled Fully Recurrent Deep Learning for Finger-Vein Verification

The DRFRDL technique comprises of three main layers namely input, hidden, output layer for accurate finger-vein authentication.  ...  However, the verification accuracy of existing algorithms was not sufficient. Also, the amount of time required for verifying the input finger vein image was more.  ...  Sample Mathematical Calculation for Verification Table I Figure.4.  ... 
doi:10.35940/ijitee.b7303.129219 fatcat:smnqt2mtdza3dlcgcfrnvmesxa

Page 2784 of Mathematical Reviews Vol. , Issue 2002D [page]

2002 Mathematical Reviews  
The goal For the web version of Mathematical Reviews, see http: //  ...  (English summary) Mathematical foundations of Computer Science 2000 ( Bratislava), 497-507, Lecture Notes in Comput. Sci., 1893, Springer, Berlin, 2000.  ... 

Page 4351 of Mathematical Reviews Vol. , Issue 2000f [page]

2000 Mathematical Reviews  
The algorithmic questions consid- ered include the usual membership problem and computability of For the web version of Mathematical Reviews, see http: //www.ams .org/mathscinet  ...  |-safe Petri nets (240- 254); Ugo Montanari and Marco Pistore, Finite state verification for the asynchronous z-calculus (255-269); Daniel Hirschkoff, On the benefits of using the up-to techniques for  ... 

Signature verification: A comprehensive study of the hidden signature method

Joanna Putz-Leszczyńska
2015 International Journal of Applied Mathematics and Computer Science  
We present a few hidden signature estimation methods together with their comprehensive comparison. The hidden signature opens a number of new possibilities for signature analysis.  ...  Traditional use of DTW for signature verification consists in forming a misalignment score between the verified signature and a set of template signatures.  ...  In each iteration, a single hidden signatureĝ estimation is computed.  ... 
doi:10.1515/amcs-2015-0048 fatcat:cpfyotcnure47jv5nomhkuptvu

Page 7544 of Mathematical Reviews Vol. , Issue 2002J [page]

2002 Mathematical Reviews  
For this purpose, a mathematical framework based on the notion of reduction is introduced.  ...  It uses one hidden function; that function is unary. But it does not use an error constant, or ex- tra (hidden) sorts, or conditional equations.  ... 

Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units [article]

Ankur Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
2021 arXiv   pre-print
Our models achieve a 1.53% average improvement over current state-of-the-art methods in equation verification and achieve a 2.22% Top-1 average accuracy and 2.96% Top-5 average accuracy for equation completion  ...  Two particular tasks that test this type of reasoning are (1) mathematical equation verification, which requires determining whether trigonometric and linear algebraic statements are valid identities or  ...  ., mathematical equation verification and equation completion, introduced in [3] . For both tasks investigated, we generated 41, 894 equations of various depths.  ... 
arXiv:2104.02899v1 fatcat:2dk2hfwutjchvc7zjeucosxc7q

A new mathematical model for diagnosing chronic diseases (kidney failure) using ANN

Adel Almarashi, Metib Alghamdi, Idir Mechai, Yuriy Rogovchenko
2019 Cogent Mathematics & Statistics  
Where, the required data for the computational health-care system is collected from various hospitals at Jazan region, Saudi Arabia.  ...  Furthermore, in order to prove the convergence of this method, a ridge function is used in the hidden layer as a basis for the neurons.  ...  Neural Network model for diagnosing kidney failure The artificial neural network (ANN) is a mathematical computational method that is used in different areas of science such as: approximation of functions  ... 
doi:10.1080/23311835.2018.1559457 fatcat:ym46jcewynh2ln3lypxyphhlai

Component-based algebraic specification and verification in cafeOBJ [chapter]

R.ăzvan Diaconescu, Kokichi Futatsugi, Shusaku Iida
1999 Lecture Notes in Computer Science  
We present a formal method for component-based system specification and verification which is based on the new algebraic specification language CafeOBJ, which is a modern successor of OBJ incorporating  ...  This methodology constitutes the basis for an industrial strength formal method around CafeOBJ.  ...  Also, add-account is related to add of Account by the projection operation for Account using the information of UserDB (client-server computing). The same holds for del-account.  ... 
doi:10.1007/3-540-48118-4_37 fatcat:whjv72oylvf5rps33rxxin52ki

A Conceptual Study on User Identification and Verification Process using Face Recognition Technique

Krishnaprasad K., P. S. Aithal
2017 International journal of applied engineering and management letters  
Face recognition system acquired great scope for the past few years in image processing for the security purposes including identification and verification process, due to its applications in various domains  ...  This paper also compares and discusses how these techniques can be used for various identification and verification system in various fields and attempts to disclose state of the art of face recognition  ...  Requires mathematical complex 3. Good for offline applications calculation. where training images are scarce. 4. Recognizes face with feature changes. Hidden 1. Better performance rate. 1.  ... 
doi:10.47992/ijaeml.2581.7000.0002 fatcat:6ebpdcpkgfdljd7lsloui7zuhe

Stochastic arithmetic and verification of mathematical models [chapter]

Jean-Marie Chesneaux, Fabienne Jézéquel, Jean-Luc Lamotte
2009 Uncertainties in Environmental Modelling and Consequences for Policy Making  
R can be modeled, at the first order with respect to 2 −p , by R ≈ r + n i=1 g i (d).2 −p .α i p is the number of bits used for the representation including the hidden bit, g i (d) are coefficients depending  ...  Theorem The loss of accuracy during a numerical computation on computer is independent of the precision used for the representation of floating point numbers.  ... 
doi:10.1007/978-90-481-2636-1_5 fatcat:32ln6krwpfeljktgnx5fk6o3ua

Intelligent encoding and economical communication in the visual stream [article]

Andras Lorincz
2004 arXiv   pre-print
The theory of computational complexity is used to underpin a recent model of neocortical sensory processing.  ...  Computational definition of the concept of intelligence is provided. Simulations illustrate the idea.  ...  In our model, verification shall play a central role for constructing the subsystems, our agents. Problem solving and verification can be related by TCC.  ... 
arXiv:q-bio/0403022v1 fatcat:vwg2jwerfvdkvnmwqkbacyytr4

TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs [article]

Houssem Ben Braiek, Foutse Khomh
2019 arXiv   pre-print
In this paper, we examine training issues in ML programs and propose a catalog of verification routines that can be used to detect the identified issues, automatically.  ...  Weights need to be initialized in a way that breaks the symmetry between hidden neurons of the same layer, because if hidden units of the same layer share the same input and output weights, they will compute  ...  One common mistake is to implement a mathematical function or to apply a wrong existing function for a layer assuming inaccurate outputs ranges.  ... 
arXiv:1909.02562v1 fatcat:xwjd2zx6sjgqjdss62rd4mg33m

Page 5104 of Mathematical Reviews Vol. , Issue 2000g [page]

2000 Mathematical Reviews  
{For the entire collection see MR 2000f:68002.} For the web version of Mathematical Reviews, see http: //  ...  Godefroid [in 8th Interna- tional Conference on Computer-aided Verification (CAV '96) (New Brunswick, NJ, 1996), \-12, Springer, Berlin, 1996].”  ... 

Modeling of reheating-furnace dynamics using neural network based on improved sequential-learning algorithm

Yingxin Liao, Min Wu, Jin-Hua She
2006 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control  
A common way of modeling reheating-furnace dynamics is to divide the furnace into zones and then to construct a mathematical model for each one.  ...  Back-propagation (BP) learning is a common technique for estimating weights for connecting hidden and output neurons, and is based on the linear least-mean-square (LMS) method.  ...  So, there is no need to compute the significance of all the hidden neurons in the network. This keeps the computational load small, as explained below. C.  ... 
doi:10.1109/cacsd-cca-isic.2006.4777146 fatcat:pg7xoxboe5g45oachwesmaz3ui
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