Neural Programming by Example

Programming by Example (PBE) targets at automatically inferring a computer program for accomplishing a certain task from sample input and output. In this paper, we propose a deep neural networks (DNN) based PBE model called Neural Programming by Example (NPBE), which can learn from input-output strings and induce programs that solve the string manipulation problems. Our NPBE model has four neural network based components: a string encoder, an input-output analyzer, a program generator, and a symbol selector. We demonstrate the effectiveness of NPBE by training it end-to-end to solve some common string manipulation problems in spreadsheet systems. The results show that our model can induce string manipulation programs effectively. Our work is one step towards teaching DNN to generate computer programs.Comment: 7 pages, Association for the Advancement of Artificial Intelligence (AAAI

Absolute height measurement of specular surfaces with modified active fringe reflection photogrammetry

Deflectometric methods have existed for more than a decade for slope measurement of specular freeform surfaces through utilization of the deformation of a sample pattern after reflection from a test surface. Usually, these approaches require two-directional fringe patterns to be projected on a LCD screen or ground glass and require slope integration, which leads to some complexity for the whole measuring process. This paper proposes a new mathematical measurement model for measuring topography information of freeform specular surfaces, which integrates a virtual reference specular surface into the method of active fringe reflection delfectometry and presents a straight-forward relation between height and phase. This method only requires one direction of horizontal or vertical sinusoidal fringe patterns to be projected on a LCD screen, resulting in a significant reduction in capture time over established method. Assuming the whole system has been pre-calibrated, during the measurement process, the fringe patterns are captured separately via the virtual reference and detected freeform surfaces by a CCD camera. The reference phase can be solved according to spatial geometrical relation between LCD screen and CCD camera. The captured phases can be unwrapped with a heterodyne technique and optimum frequency selection method. Based on this calculated unwrapped-phase and that proposed mathematical model, absolute height of the inspected surface can be computed. Simulated and experimental results show that this methodology can conveniently calculate topography information for freeform and structured specular surfaces without integration and reconstruction processes

Relay Selection for Bidirectional AF Relay Network with Outdated CSI

Most previous researches on bidirectional relay selection (RS) typically assume perfect channel state information (CSI). However, outdated CSI, caused by the the time-variation of channel, cannot be ignored in the practical system, and it will deteriorate the performance. In this paper, the effect of outdated CSI on the performance of bidirectional amplify-and-forward RS is investigated. The optimal single RS scheme in minimizing the symbol error rate (SER) is revised by incorporating the outdated channels. The analytical expressions of end-to-end signal to noise ratio (SNR) and symbol error rate (SER) are derived in a closed-form, along with the asymptotic SER expression in high SNR. All the analytical expressions are verified by the Monte-Carlo simulations. The analytical and the simulation results reveal that once CSI is outdated, the diversity order degrades to one from full diversity. Furthermore, a multiple RS scheme is proposed and verified that this scheme is a feasible solution to compensate the diversity loss caused by outdated CSI.Comment: accepted by IEEE Transactions on Vehicular Technolog