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書目名稱Geometric Algebra Applications Vol. III影響因子(影響力)




書目名稱Geometric Algebra Applications Vol. III影響因子(影響力)學科排名




書目名稱Geometric Algebra Applications Vol. III網(wǎng)絡公開度




書目名稱Geometric Algebra Applications Vol. III網(wǎng)絡公開度學科排名




書目名稱Geometric Algebra Applications Vol. III被引頻次




書目名稱Geometric Algebra Applications Vol. III被引頻次學科排名




書目名稱Geometric Algebra Applications Vol. III年度引用




書目名稱Geometric Algebra Applications Vol. III年度引用學科排名




書目名稱Geometric Algebra Applications Vol. III讀者反饋




書目名稱Geometric Algebra Applications Vol. III讀者反饋學科排名

faultfinder

2D, 3D, and 4D Geometric Algebrase Aragand’s achievement was an interpretation of . as a rotation by a right angle in the plane. Complex numbers received their name by Gauss and their formal definition as pair of real numbers was introduced by Hamilton in 1835.

皮薩

Kinematics of the 2D and 3D Spacesng 3D and 4D geometric algebras, the classic?model for the 3D motion of vectors. Finally, we compare both models, that is, the one using 3D Euclidean geometric algebra and our model, which uses 4D motor algebra.

Astigmatism

The Geometric Algebras ,, ,, ,, es, and planes using vector calculus, . and . in Chap. 7 of?[.]. Extending the degrees of freedom of the mathematical system, in the conformal geometric algebra?., using the horosphere framework points, one can model lines, planes, circles, and spheres and also certain Lie groups as a versors.

Assault

Geometric Neural Computinghows that real-, complex-,?and quaternion-valued neural networks are simply particular cases of geometric algebra multidimensional neural networks and that some can be generated using support multivector machines.

冒煙

冒煙

悲痛

Cardioplegia

https://doi.org/10.1007/978-3-663-05492-4rts. The improvement in the classification rate of the neural network classifiers is very encouraging, which amply justifies the preprocessing in the quaternion frequency domain. This work also suggests the application of the quaternion Fourier transform for other image processing tasks.

步履蹣跚

Applications of?Quaternion Fourier and?Wavelet Transforms, and?Radon Transformrts. The improvement in the classification rate of the neural network classifiers is very encouraging, which amply justifies the preprocessing in the quaternion frequency domain. This work also suggests the application of the quaternion Fourier transform for other image processing tasks.