In this paper, cognitive radio and simultaneous wireless information and power transfer (SWIPT) are effectively combined to design a spectrum‐efficient and energy‐efficient transmission paradigm. Specifically, a novel SWIPT‐based primary‐secondary cooperation model is proposed to increase the transmission rate of energy/spectrum constrained users. In the proposed model, a multi‐antenna secondary user conducts simultaneous energy harvesting and information forwarding by means of power splitting (PS), and tries to maximize its own transmission rate under the premise of successfully assisting the data delivery of the primary user. After the problem formulation, joint power splitting and beamforming optimization algorithms for decode‐and‐forward and amplify‐and‐forward modes are presented, in which we obtain the optimal PS factor and beamforming vectors using a golden search method and dual methods. Simulation results show that the proposed SWIPTbased primary‐secondary cooperation schemes can obtain a much higher level of performance than that of non‐SWIPT cooperation and non‐cooperation schemes.

Wavelet neural network(WNN) was applied to predicate the cortisol solubility. The model consists of a multilayer feedforward hierarchical structure, and the flow of information is directed from the input to the output layer by using wavelet transforms to achieve faster convergence. By adaptively adjusting the number of training data involved during training, an adaptive robust learning algorithm is derived for improvement of the efficiency of the network. The neural network was trained and simulated cortisol solubility with different input and output parameters. Simulation results confirmed that this approach gave more accurate predictions solubility.