The usefulness of an artificial analog neural network is closely bound to its trainability. This paper introduces a new analog neural network architecture using weights determined by a genetic algorithm. The first VLSI implementation presented in this paper achieves 200 giga connections per second with 4096 synapses on less than 1 mm silicon area. Since the training can be done at the full spee...

This paper presents the results of experiments on probabilistic GLR (PGLR), a new probabilistic model proposed by (Inui et al., 1997). The model is formalized based on stack transition during parsing distinguishing it from the existing models proposed byWright andWrigley, and Briscoe and Carroll. Our model produces a remarkable improvement in syntactic parsing with probability. Associating prob...

We introduce MinimalRNN, a new recurrent neural network architecture that achieves comparable performance as the popular gated RNNs with a simplified structure. It employs minimal updates within RNN, which not only leads to efficient learning and testing but more importantly better interpretability and trainability. We demonstrate that by endorsing the more restrictive update rule, MinimalRNN l...

In this paper, we develop a novel modeling scheme for discrete-mixture HMMs (DMHMMs) by using maximum a posteriori (MAP) estimation. Also the MAP estimated DMHMMs are used for speech recognition to improve the accuracy under noisy conditions. The DMHMMs were originally proposed to reduce calculation costs in decoding process [1][2]. We propose a new method for MAP estimation of DMHMM parameters...

We investigate the relationship between characteristics of dog breeds and their popularity between years 1926 and 2005. We consider breed health, longevity, and behavioral qualities such as aggressiveness, trainability, and fearfulness. We show that a breed's overall popularity, fluctuations in popularity, and rates of increase and decrease around popularity peaks show typically no correlation ...

Domestic dogs (Canis lupus familiaris) are one of the most morphologically varied species, exhibiting an enormous variety of sizes and body types. Different breeds also exhibit different behavioural traits, and are perceived by dog trainers and owners as having variable abilities to be trained. There is evidence of a strong genetic component in canine behaviour. However, recent studies suggest ...

THE DEVELOPMENT OF PHYSICAL FITNESS IN YOUNG ATHLETES IS A RAPIDLY EXPANDING FIELD OF INTEREST FOR STRENGTH AND CONDITIONING COACHES, PHYSICAL EDUCATORS, SPORTS COACHES, AND PARENTS. PREVIOUS LONG-TERM ATHLETE DEVELOPMENT MODELS HAVE CLASSIFIED YOUTH-BASED TRAINING METHODOLOGIES IN RELATION TO CHRONOLOGIC AGE GROUPS, AN APPROACH THAT HAS DISTINCT LIMITATIONS. MORE RECENT MODELS HAVE ATTEMPTED T...

Oneof themost efficientmethods to reduce the dropping andblockingprobabilities of the secondary users (SUs) in cognitive radio networks is channel sub-banding strategy. This means that when all the channels are occupied by the primary and secondary users, then the SUs’ channels can be divided into two sub-bands, and two SUs can use a subband, simultaneously. In this paper, we propose an opportu...

In this paper, we study a coalitional game approach to resource allocation in a multi-channel cooperative cognitive radio network with multiple primary users (PUs) and secondary users (SUs). We propose to form the grand coalition by grouping all PUs and SUs in a set, where each PU can lease its spectrum to all SUs in a time-division manner while the SUs in return assist PUs’ data transmission a...