The radial basis function network offers a viable alternative to the two-layer neural network in many applications of signal processing. A common learning algorithm for radial basis function networks is based on first choosing randomly some data points as radial basis function centers and then using singular-value decomposition to solve for the weights of the network. Such a procedure has several drawbacks, and, in particular, an arbitrary selection of centers is clearly unsatisfactory. The authors propose an alternative learning procedure based on the orthogonal least-squares method. The procedure chooses radial basis function centers one by one in a rational way until an adequate network has been constructed. In the algorithm, each selected center maximizes the increment to the explained variance or energy of the desired output and does not suffer numerical ill-conditioning problems. The orthogonal least-squares learning strategy provides a simple and efficient means for fitting radial basis function networks. This is illustrated using examples taken from two different signal processing applications.

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Fuel cells are clean, sustainable energy conversion devices for power generation, and they most commonly use platinum as the electrocatalyst.[1] However, Pt-based catalysts suffer from very limited reserves, high cost, and inactivation by CO poisoning; these are major obstacles that fuel cells have to overcome for commercialization. [1][2][3][4][5][6] Thus, exploring nonprecious metal or even metal-free catalysts to rival platinum in activity and durability is absolutely crucial, with a potentially revolutionary impact on fuel-cell technologies. Very recently, metal-free PEDOT [6] and nitrogen-doped carbon nanotubes (NCNTs) [7,8] have shown a striking electrocatalytic performance for the oxygen reduction reaction (ORR). These breakthroughs have activated an exciting field for exploring the advanced metal-free electrocatalysts and understanding the related mechanism.As one of the most important carbon nanostructures, carbon-based nanotubes have been widely studied as the support of electrocatalysts for fuel cells in recent years. [9][10][11][12] Recent progress involving doping carbon nanotubes (CNTs) with electron-rich nitrogen to transform CNTs into superb metal-free electrocatalysts for the ORR [7,8] has motivated our curiosity to examine the corresponding performance of its counterpart by doping CNTs with electron-deficient boron. Intuitively, the adsorption of O 2 on boron dopant should be quite easy owing to the large difference of electronegativity between boron and oxygen, which is the precondition for the subsequent O 2 dissociation. In this study, BCNTs with tunable boron content of 0-2.24 atom % were synthesized. The ORR onset and peak potentials shift positively and the current density increases noticeably with increasing boron content, indicating a strong dependence of the ORR performance on boron content. Moreover, the origin of the electrocatalytic activity of BCNTs including the role of the boron dopant has been revealed by density functional theory (DFT) calculations. The experimental and theoretical results provide a new strategy to explore carbon-based metal-free electrocatalysts that are significant to the development of fuel cells.Using chemical vapor deposition (CVD) with benzene, triphenylborane (TPB), and ferrocene as precursors and catalyst, BCNTs were synthesized with tunable boron content of 0-2.24 at % by using different TPB concentrations. BCNTs with boron content of 0.86, 1.33, and 2.24 at %, as determined by X-ray photoelectron spectroscopy (XPS), were denoted as B 1 CNTs, B 2 CNTs, and B 3 CNTs, respectively (Supporting Information, S1

Abstract-In the 5th generation (5G) of wireless communication systems, hitherto unprecedented requirements are expected to be satisfied. As one of the promising techniques of addressing these challenges, non-orthogonal multiple access (NOMA) has been actively investigated in recent years. In contrast to the family of conventional orthogonal multiple access (OMA) schemes, the key distinguishing feature of NOMA is to support a higher number of users than the number of orthogonal resource slots with the aid of non-orthogonal resource allocation. This may be realized by the sophisticated inter-user interference cancellation at the cost of an increased receiver complexity. In this article, we provide a comprehensive survey of the original birth, the most recent development, and the future research directions of NOMA. Specifically, the basic principle of NOMA will be introduced at first, with the comparison between NOMA and OMA especially from the perspective of information theory. Then, the prominent NOMA schemes are discussed by dividing them into two categories, namely, power-domain and code-domain NOMA. Their design principles and key features will be discussed in detail, and a systematic comparison of these NOMA schemes will be summarized in terms of their spectral efficiency, system performance, receiver complexity, etc. Finally, we will highlight a range of challenging open problems that should be solved for NOMA, along with corresponding opportunities and future research trends to address these challenges.

Two kinds of boron and nitrogen co-doped carbon nanotubes (CNTs) dominated by bonded or separated B and N are intentionally prepared, which present distinct oxygen reduction reaction (ORR) performances. The experimental and theoretical results indicate that the bonded case cannot, while the separated one can, turn the inert CNTs into ORR electrocatalysts. This progress demonstrates the crucial role of the doping microstructure on ORR performance, which is of significance in exploring the advanced C-based metal-free electrocatalysts.