We propose a novel method to enhance the short-term memory of spin-wave-based reservoir computing (RC) systems by tilting the external magnetic field. The tilting of the field modifies the interaction between two spin-wave modes, enabling simultaneous propagation of both backward volume spin waves (BVSWs) and surface spin waves (SSWs). We present this system as an alternative realization of multiple-mode coexisting (MMC) structures. First, our numerical comparison of BVSWs and SSWs demonstrates distinct group velocities between these two modes. We then evaluate the spin-wave reservoir’s performance on a delay task under different magnetic field orientations, revealing that the MMC structure achieves a higher memory capacity than conventional single-mode configurations. Furthermore, in a temporal exclusive-OR (XOR) task, the MMC structure not only improves the performance accuracy but also supports longer delay times compared to single-mode setups. These findings underscore the critical role of field orientation in enhancing spin-wave RC performance and offer insights into practical implementations of spin-wave reservoir designs.

We propose a novel spin-wave-based reservoir computing (RC) chip-and-antenna structure that utilizes two coexisting magnetostatic modes. In our structure, both backward volume spin waves (BVSW) and surface spin waves (SSW) simultaneously arise and propagate in a magnetic film, leading to enhanced nonlinearity. We name this type of setup multiple-mode coexisting (MMC) structures. First in numerical analysis of MMC structure, we examine the frequency spectrum of the output signals and quantify the degree of nonlinearity. We then perform a signal transformation task to evaluate the nonlinearity enhanced in our MMC structure. Our results show that the use of two modes significantly enhances the even and odd harmonics and achieves a high performance improvement index up to 25.4% compared to 5% in conventional single-mode cases. The results demonstrate the enhanced nonlinearity of the MMC structure, which is essential not only for improving the performance of spin-wave-based RC systems but also for enabling the practical implementation of spin-wave reservoir chips.

Estimating abundance fraction of materials in hyperspectral images is an important area of study in the field of remote sensing. The need for fraction estimation in remotely sensed images arises from the fact that the sampling distance is generally larger than the size of the targets of interest. The abundance sum-to-one constraint and the abundance nonnegativity constraint are the two physical constraints often considered when developing estimation methods. In this paper, we relax the abundance sum-to-one constraint as this condition is rarely satisfied in reality and use the relaxed sum-to-one constraint instead to develop a constrained method. Experimental results demonstrate that this method provides more precise estimation of the fractions when the sum-to-one constraint is violated, while producing similar results to other existing methods when the constraint holds.