: ‘ Introduction to complex-valued matrix differentiation ’, IEEE Trans. Signal Process. , 2007 , 55 , pp. 2740 – 2746 .A. Hjorungnes, D. Gesbert, and D. P. Palomar, "Unified theory of com- plex-valued matrix differentiation," in Proc. IEEE Int. Conf. Acoust., Speech Signal ...
The matrix-flattening methods, device parameters, and signal processing flow remained consistent with demonstrations in the above section for input data Xa. The experi- mental results closely matched with in-silico results, except for that our CVOCA's input data rate was at 14.245 GBaud — over...
Complex-Valued Matrix Differentiation: Techniques and Key Results A systematic theory is introduced for finding the derivatives of complex-valued matrix functions with respect to a complex-valued matrix variable and the c... A Hjorungnes,D Gesbert - 《IEEE Transactions on Signal Processing》 被引...
Complex-valued matrix convolution In the experimental demonstration of our CVOCA, a key building block is the soliton crystal microcomb source that yielded tens of wavelength channels for the mapping of the complex-valued convolutional kernel weights W (Fig. 3). The employed soliton crystal microco...
In this paper, the use of complex differentiation is presented as a robust and concise tool for modeling and sensitivity analysis of large-scale electrical networks. A complex power flow model was employed to determine the network’s operating point, from which the sensitivity analysis of the elec...
(4), the update of output weights requires the differentiation of the E function with respect to ωkj which allows us to obtain the following equation: ∂E ∂ωkj = −φj ∂E ∂yk ⇔ Δωkj ∂E = αφj ∂yk (6) where Δ is the delta rule, i.e., a gradient ...