A compact image-capturing system called TOMBO (an acronym for thin observation module by bound optics) is presented in which the compound-eye imaging system is utilized to achieve a thin optical configuration. The captured multiple images are processed to retrieve the image of the target object. For image retrieval, two kinds of processing method are considered: image sampling and backprojection. Computer simulations and preliminary experiments were executed on an evaluation system to verify the principles of the system and to clarify the issues related to its implementation.

There has been an increasing interest in the application of terahertz (THz) waves to broadband wireless communications. In particular, use of frequencies above 275 GHz is one of the strong concerns among radio scientists and engineers, because these frequency bands have not yet been allocated at specific active services, and there is a possibility to employ extremely large bandwidths for ultra-broadband wireless communications. Introduction of photonics technologies for signal generation, modulation and detection is effective not only to enhance the bandwidth and/or the data rate, but also to combine fiber-optic (wired) and wireless networks. This paper reviews recent progress in THz wireless communications using telecom-based photonics technologies towards 100 Gbit/s.

We present a machine-learning-based method for single-shot imaging through scattering media. The inverse scattering process was calculated based on a nonlinear regression algorithm by learning a number of training object-speckle pairs. In the experimental demonstration, multilayer phase objects between scattering plates were reconstructed from intensity measurements. Our approach enables model-free sensing, where it is not necessary to know the sensing processes/models.

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This paper proposes a parallel distributed processing model with local space-invariant interconnections, which is more readily implemented by optics and is able to classify patterns correctly, even if they have been shifted or distorted. Error backpropagation is used as a training algorithm. Computer simulation results presented indicate that the processing is effective and the network can deal with the shifted or distorted patterns. Moreover, the optical implementation architecture using matched filters for the model is discussed.