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위키데이터
- ID : Q27670
말뭉치
- An alternative—but entirely equivalent and often simpler—definition of linear independence reads as follows.[1]
- If a collection of vectors from R n contains more than n vectors, the question of its linear independence is easily answered.[1]
- It is a long answer but kindly bear with me To understand linear dependence and linear independence we first need to understand linear combination and span.[2]
- A geographic example may help to clarify the concept of linear independence.[3]
- Requiring orthogonality or linear independence of expansion vectors imposes considerable constraints which are often in conflict with application-related specifications.[4]
- Note that linear dependence and linear independence are notions that apply to a collection of vectors.[5]
- We are now going to define the notion of linear independence of a list of vectors.[6]
- So hopefully, you're starting to see the relationship between span and linear independence or linear dependence.[7]
- Linear Independence and the Wronskian Recall from linear algebra that two vectors v and w are called linearly dependent if there are nonzero constants c 1 and c 2 with.[8]
- Our proof uses Padé approximation following the argument of T. Rivoal, however we adapt a new linear independence criterion due to S. Fischler and W. Zudilin.[9]
- " This will show us a symbolic example of such vectors with the notation used in the linear independence calculator.[10]
- Once we input the last number, the linear independence calculator will instantly tell us if we have linearly independent vectors or not, and what is the dimension of the span of the vectors.[10]
- Fortunately, we have the linear independence calculator at hand and can play around with the vectors to find a suitable vector combination.[10]
- However, linear independence can’t always be represented in 2D space.[11]
- If we want to be able to define a unique model, then we will care about the linear independence of the basis set.[11]
- We investigate the condition which ensures linear independence of the plane waves.[12]
- In the case all the three procedures are combined, the linear independence can be proved by ad hoc methods for most of commonly used activation functions.[12]
- One of the key differences between the deterministic linear network coding technique (DLNC) and the RLNC is that the RLNC coding coefficients increase the probability of their linear independence .[13]
- Further improvements include the formalization of linear combinations, linear dependence, linear independence , and subspace.[13]
- Much ado gets made about linear independence, probably because it makes up quite a few questions where the answer is not immediately obvious.[14]
- The next result rephrases the linear independence definition in this style.[15]
- That leaves one case, whether linear independence is preserved by superset.[15]
- In developing this table we've uncovered an intimate relationship between linear independence and span.[15]
- In summary, we have introduced the definition of linear independence to formalize the idea of the minimality of a spanning set.[15]
소스
- ↑ 1.0 1.1 Linear Independence
- ↑ What exactly does linear dependence and linear independence imply?
- ↑ Linear independence
- ↑ Linear Independence - an overview
- ↑ Linear Independence
- ↑ 5.2: Linear Independence
- ↑ Introduction to linear independence (video)
- ↑ Linear Independence and the Wronskian
- ↑ Hirata-Kohno , Okada : A note on linear independence of polylogarithms over the rationals
- ↑ 10.0 10.1 10.2 Linear Independence Calculator
- ↑ 11.0 11.1 Linearly Independent Vectors
- ↑ 12.0 12.1 Nonlinearity creates linear independence
- ↑ 13.0 13.1 linear independence
- ↑ Linear Algebra
- ↑ 15.0 15.1 15.2 15.3 Linear Algebra/Definition and Examples of Linear Independence
메타데이터
위키데이터
- ID : Q27670
Spacy 패턴 목록
- [{'LOWER': 'linear'}, {'LEMMA': 'independence'}]