Let ? be an open connected subset of the complex plane C and let T be a bounded linear operator on a Hilbert space H. For ? in ? let e the orthogonal projection onto the null-space of T-?I . We discuss the necessary and sufficient conditions for the map ?? to b e continuous on ?. A generalized Gram- Schmidt process is also given.

Unknown faults may occur in practical applications, necessitating an open-set classifier that can classify known classes as well recognize unknown faults. The current deep classification methods are implicit optimizing the intra- or inter-class distances, which result performance degradation when number of far exceeds known. In this study, discriminative angle features for vibration signals inv...

Open-set signal recognition provides a new approach for verifying the robustness of models by introducing novel unknown classes into model testing and breaking conventional closed-set assumption, which has become very popular in real-world scenarios. In present work, we propose an efficient open-set algorithm, contains three key sub-modules: representation sub-module based on vision transformer...

As the essential content of intelligent animal husbandry, identifying each livestock is only way to achieve modern and refined scientific husbandry. This paper proposes a sheep face recognition method based on European spatial metrics realizes noncontact identity by training network using image samples in natural environment. The SheepBase data set was first proposed this process, which contain...

Open set classification (OSC) tackles the problem of determining whether data are in-class or out-of-class during inference, when only provided with a examples at training time. Traditional OSC methods usually train discriminative generative models owned data, and then utilize pre-trained to classify test directly. However, these always suffer from embedding confusion problem, i.e., partial ins...

Abstract Aiming at the problem of multi-view high-resolution range profile (HRRP) target recognition under open set conditions, we proposed an method based on joint sparse representation (JSR), which solves low rate traditional methods conditions. This is applied to background radar single-station observation. JSR used solve reconstruction error HRRP by over-complete dictionary, while extreme v...