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algebra 音標拼音: ['ældʒəbrə] n. 代數學 代數學 algebra代數 algebra n 1: the mathematics of generalized arithmetical operationsMathematics \ Math` e* mat" ics\, n. [ F. math[' e] matiques, pl., L. mathematica, sing., Gr. ? ( sc. ?) science. See { Mathematic}, and {- ics}.] That science, or class of sciences, which treats of the exact relations existing between quantities or magnitudes, and of the methods by which, in accordance with these relations, quantities sought are deducible from other quantities known or supposed; the science of spatial and quantitative relations. [ 1913 Webster] Note: Mathematics embraces three departments, namely: 1. { Arithmetic}. 2. { Geometry}, including { Trigonometry} and { Conic Sections}. 3. { Analysis}, in which letters are used, including { Algebra}, { Analytical Geometry}, and { Calculus}. Each of these divisions is divided into pure or abstract, which considers magnitude or quantity abstractly, without relation to matter; and mixed or applied, which treats of magnitude as subsisting in material bodies, and is consequently interwoven with physical considerations. [ 1913 Webster]
Algebra \ Al" ge* bra\, n. [ LL. algebra, fr. Ar. al- jebr reduction of parts to a whole, or fractions to whole numbers, fr. jabara to bind together, consolidate; al- jebr w' almuq[= a] balah reduction and comparison ( by equations): cf. F. alg[` e] bre, It. & Sp. algebra.] 1. ( Math.) That branch of mathematics which treats of the relations and properties of quantity by means of letters and other symbols. It is applicable to those relations that are true of every kind of magnitude. [ 1913 Webster] 2. A treatise on this science. [ 1913 Webster] Algebraic 1. A loose term for an {algebraic
structure}.
2. A {vector space} that is also a {ring}, where the vector
space and the ring share the same addition operation and are
related in certain other ways.
An example algebra is the set of 2x2 {matrices} with {real
numbers} as entries, with the usual operations of addition and
matrix multiplication, and the usual {scalar} multiplication.
Another example is the set of all {polynomials} with real
coefficients, with the usual operations.
In more detail, we have:
(1) an underlying {set},
(2) a {field} of {scalars},
(3) an operation of scalar multiplication, whose input is a
scalar and a member of the underlying set and whose output is
a member of the underlying set, just as in a {vector space},
(4) an operation of addition of members of the underlying set,
whose input is an {ordered pair} of such members and whose
output is one such member, just as in a vector space or a
ring,
(5) an operation of multiplication of members of the
underlying set, whose input is an ordered pair of such members
and whose output is one such member, just as in a ring.
This whole thing constitutes an `algebra' iff:
(1) it is a vector space if you discard item (5) and
(2) it is a ring if you discard (2) and (3) and
(3) for any scalar r and any two members A, B of the
underlying set we have r(AB) = (rA)B = A(rB). In other words
it doesn't matter whether you multiply members of the algebra
first and then multiply by the scalar, or multiply one of them
by the scalar first and then multiply the two members of the
algebra. Note that the A comes before the B because the
multiplication is in some cases not commutative, e.g. the
matrix example.
Another example (an example of a {Banach algebra}) is the set
of all {bounded} {linear operators} on a {Hilbert space}, with
the usual {norm}. The multiplication is the operation of
{composition} of operators, and the addition and scalar
multiplication are just what you would expect.
Two other examples are {tensor algebras} and {Clifford
algebras}.
[I. N. Herstein, "Topics in Algebra"].
(1999-07-14)
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