Competitive learning is a general technique for training clustering and classification networks. We have developed an 11-transistor silicon circuit, that we term an automaximizing bump circuit, that uses silicon physics to naturally implement a similarity computation, local adaptation, simultaneous adaptation and computation and nonvolatile storage. This circuit is an ideal building block for constructing competitive-learning networks. We illustrate the adaptive nature of the automaximizing bump in two ways. First, we demonstrate a silicon competitive-learning circuit that clusters one-dimensional (1-D) data. We then illustrate a general architecture based on the automaximizing bump circuit; we show the effectiveness of this architecture, via software simulation, on a general clustering task. We corroborate our analysis with experimental data from circuits fabricated in a 0.35-/spl mu/m CMOS process.

Multiplexing is a strategy to augment the transmission capacity of a communication system. It consists of combining multiple signals over the same data channel and it has been very successful in classical communications. However, the use of enhanced channels has only reached limited practicality in quantum communications (QC) as it requires the manipulation of quantum systems of higher dimensions. Considerable effort is being made towards QC using high-dimensional quantum systems encoded into the transverse momentum of single photons, but so far no approach has been proven to be fully compatible with the existing telecommunication fibers. Here we overcome such a challenge and demonstrate a secure high-dimensional decoy-state quantum key distribution session over a 300-m-long multicore optical fiber. The high-dimensional quantum states are defined in terms of the transverse core modes available for the photon transmission over the fiber, and theoretical analyses show that positive secret key rates can be achieved through metropolitan distances.

Human brain connectivity is extremely complex and variable across subjects. While long association and projection bundles are stable and have been deeply studied, short association bundles present higher intersubject variability, and few studies have been carried out to adequately describe the structure, shape, and reproducibility of these bundles. However, their analysis is crucial to understand brain function and better characterize the human connectome. In this study, we propose an automatic method to identify reproducible short association bundles of the superficial white matter, based on intersubject hierarchical clustering. The method is applied to the whole brain and finds representative clusters of similar fibers belonging to a group of subjects, according to a distance metric between fibers. We experimented with both affine and non-linear registrations and, due to better reproducibility, chose the results obtained from non-linear registration. Once the clusters are calculated, our method performs automatic labeling of the most stable connections based on individual cortical parcellations. We compare results between two independent groups of subjects from a HARDI database to generate reproducible connections for the creation of an atlas. To perform a better validation of the results, we used a bagging strategy that uses pairs of groups of 27 subjects from a database of 74 subjects. The result is an atlas with 44 bundles in the left hemisphere and 49 in the right hemisphere, of which 33 bundles are found in both hemispheres. Finally, we use the atlas to automatically segment 78 new subjects from a different HARDI database and to analyze stability and lateralization results.

Any practical realization of entanglement-based quantum communication must be intrinsically secure and able to span long distances avoiding the need of a straight line between the communicating parties. The violation of Bell's inequality offers a method for the certification of quantum links without knowing the inner workings of the devices. Energy-time entanglement quantum communication satisfies all these requirements. However, currently there is a fundamental obstacle with the standard configuration adopted: an intrinsic geometrical loophole that can be exploited to break the security of the communication, in addition to other loopholes. Here we show the first experimental Bell violation with energy-time entanglement distributed over 1 km of optical fibres that is free of this geometrical loophole. This is achieved by adopting a new experimental design, and by using an actively stabilized fibre-based long interferometer. Our results represent an important step towards long-distance secure quantum communication in optical fibres.

This paper examines reconfigurable pipelined datapaths (RaPiDs), a new architecture style for computation-intensive applications that bridges the cost/performance gap between general purpose and application specific architectures. RaPiDs can provide significantly higher performance than general purpose processors on a wide range of applications from the areas of video and signal processing, scientific computing and communications. Moreover, RaPiDs provide the flexibility that does not come with application-specific architectures. A RaPiD architecture is optimized for highly repetitive, computationally-intensive tasks. Very deep application-specific computation pipelines can be configured that deliver very high performance for a wide range of applications. RaPiDs achieve this using a coarse-grained reconfigurable architecture that mixes the appropriate amount of static configuration with dynamic control. We describe the fundamental features of a RaPiD architecture, including the linear array of functional units, a programmable segmented bus structure, and a programmable control architecture. In addition, we outline the floorplan of the architecture and provide timing data for the most critical paths. We conclude with performance numbers for several applications on an instance of a RaPiD architecture.

Digital signal processors (DSPs) and field-programmable gate arrays (FPGAs) are predominant in the implementation of digital controllers and/or modulators for power converter applications. This paper presents a systematic comparison between these two technologies, depicting the main advantages and drawbacks of each one. Key programming and implementation aspects are addressed in order to give an overall idea of their most important features and allow the comparison between DSP and FPGA devices. A classical linear control strategy for a well-known voltage-source-converter (VSC)-based topology used as Static Compensator (STATCOM) is considered as a driving example to evaluate the performance of both approaches. A proof-of-concept laboratory prototype is separately controlled with the TMS320F2812 DSP and the Spartan-3 XCS1000 FPGA to illustrate the characteristics of both technologies. In the case of the DSP, a virtual floating-point library is used to accelerate the control routines compared to double precision arithmetic. On the other hand, two approaches are developed for the FPGA implementation, the first one reduces the hardware utilization and the second one reduces the computation time. Even though both boards can successfully control the STATCOM, results show that the FPGA achieves the best computation time thanks to the high degree of parallelism available on the device.