Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userLinear Systems Analysis Methods
طرائق تحليل الأنظمة الخطية بمصفوفات معاملات غير كثيفة
1180
0 6
0
(
0
)
Added by
Damascus University ورقة بحثية
Publication date
1998
fields
Mathematics
and research's language is
العربية
Created by
Shamra Editor
Ask ChatGPT about the research
يهدف البحث الى دراسة خواص الجمل الخطية باستعمال البيانات الموجهة و البنى العددية، و إيجاد خوارزميات فعالة تحدد العدد التقريبي للحدود اللاصفرية في مفكوك محددات مصفوفاتها، و تعتمد هذه الخوارزميات على أشجار تمثل البنى العددية الحاوية مؤشرات الحدود اللاصفرية. تم التوصل في هذا البحث الى نتائج مهمة تخدم التطبيقات الهندسية العملية المستعملة للجمل الخطية بمصفوفات غير كثيفة مثل الشبكات و الدارات الالكترونية، و علب السرع الأرضية، و الجمل متعددة الأعمال و غيرها.
In this paper we consider the properties of linear systems by means of directed graphs and numerical structures. We also state efficient algorithms for determining an approximate number of the non-zero terms within determinants' expressions of their matrices. The stated algorithms make use of trees representing numerical structures which contains the indices of the nonzero terms. This paper yields interesting results used in practical engineering applications which include linear systems with sparse matrices, for example: networks, electronic circuits, earth velocities boxes (gearboxes), multi-works systems ...etc.
References used
ايرامس، تحليل دارات الآلات الالكترونية بوساطة البيانات، دار مير، موسكو 1986
ف.س.لينسكي وأ.يو.سشكوف، مراقبة الخواص الهندسية لعلب السرع الأرضية، مجلة التقانات . الحاسوبية لبناء الآلات، مينسك، 1972
أ.يو.سشكوف، بيانات الآلات المسننة، لينغراد ١٩٨٣
rate research
Read More
In this Searching scientific, , we introduced three methods for
finding the solution of pentadiagonal linear systems of equations.
This paper presents a method for finding online adaptive optimal
controllers for continuous-time linear systems without knowing the
system dynamical matrices. The proposed method employs one of
Intelligent Operations Research Techniques, this tech
nique is the
adaptive dynamic programming, to iteratively solve the algebraic
Riccati equation using the online information of state and input,
without requiring the a priori knowledge of the system dynamics. In
addition, all iterations can be conducted by using repeatedly the
same state and input information on some fixed time intervals. A
practical online algorithm is developed in this paper, and is applied
to the controller design for a turbocharged diesel engine with
exhaust gas recirculation.
In this research, we investigate a problem of controllable and observerable for linear Continuous-time systems.
We have founded controllable and observerable conditions for the linear continuous-time system. Moreover, we put out a new algorithm for
finding control vector of steps that can enable us to move the state vector from the initial stage x(0) into the final onex(tf) for finite time tf>0, the theoretical results is illustrated by an example. Finally,we put program to plot trajectory of state vector x(t) and observer vector y(t)
In this paper, we present two new methods for finding
the numerical solutions of systems of the nonlinear equations.
The basic idea depend on
founding relationship between minimum of a function and the
solution of systems of the nonlinear equatio
ns. The first method
seeks the numerical solution with a sequence of search
directions, which is depended on gradient and Hessian matrix of
function, while the second method is based on a sequence of
conjugate search directions. The study shows that our two
methods are convergent, and they can find exact solutions for
quadratic functions, so they can find high accurate solutions for
over quadratic functions. The purposed two algorithms are
programmed by Mathematica Version9. The approximate
solutions of some test problems are given. Comparisons of our
results with other methods illustrate the efficiency and highly
accurate of our suggested methods.
Probes are models devised to investigate the encoding of knowledge---e.g. syntactic structure---in contextual representations. Probes are often designed for simplicity, which has led to restrictions on probe design that may not allow for the full exp
loitation of the structure of encoded information; one such restriction is linearity. We examine the case of a structural probe (Hewitt and Manning, 2019), which aims to investigate the encoding of syntactic structure in contextual representations through learning only linear transformations. By observing that the structural probe learns a metric, we are able to kernelize it and develop a novel non-linear variant with an identical number of parameters. We test on 6 languages and find that the radial-basis function (RBF) kernel, in conjunction with regularization, achieves a statistically significant improvement over the baseline in all languages---implying that at least part of the syntactic knowledge is encoded non-linearly. We conclude by discussing how the RBF kernel resembles BERT's self-attention layers and speculate that this resemblance leads to the RBF-based probe's stronger performance.
suggested questions
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
