s For the on-line safe path planning of a mobile robot in unknown environments, the paper proposes a simple Hopfield Neural Network ( HNN ) planner. Without learning process, the HNN plans a safe path with consideration of “ too close” or “ too far” . For obstacles of arbitrary shape, we prove that the HNN has no unexpected local attractive point and can find a steepest climbing path, if a feas...

Several studies have linked cilia and Hedgehog signaling, but the precise roles of ciliary proteins in signal transduction remain enigmatic. Here we describe a mouse mutation, hennin (hnn), that causes coupled defects in cilia structure and Sonic hedgehog (Shh) signaling. The hnn mutant cilia are short with a specific defect in the structure of the ciliary axoneme, and the hnn neural tube shows...

This paper presents the locomotion control of a microelectromechanical system (MEMS) microrobot. The MEMS microrobot demonstrates locomotion control by pulse-type hardware neural networks (P-HNN). P-HNN generate oscillatory patterns of electrical activity like those of living organisms. The basic component of P-HNN is a pulse-type hardware neuron model (P-HNM). The P-HNM has the same basic feat...

Hexapod locomotive Micro-Electro Mechanical Systems (MEMS) microrobot with Pulse-type Hardware Neural Networks (P-HNN) locomotion controlling system is presented in this chapter. MEMS microrobot is less than 5 mm width, length, and height in size. MEMS microrobot is made from a silicon wafer fabricated by micro fabrication technology to realize the small size mechanical components. The mechanic...

In Orthogonal frequency division multiplexing (OFDM) transmission system, channel variations within an OFDM symbol destroy orthogonality between subcarriers, resulting in intercarrier interference (ICI), which increases an error floor in proportional to normalized Doppler frequency. To mitigate the effects of channel variations, in this paper, we propose a novel ICI suppression technique, which...

3.3. The greatest common divisor and the least common multiple 12 3.4. Parabolic divisors 14 3.5. Divisibility: further properties 14 4. Normal forms arising from HNN extensions 16 4.1. HNN -normal form 16 5. Conjugacy problem 18 5.1. Conjugacy Criterion for HNN -extensions 18 5.2. Block decomposition 22 5.3. Conjugacy with respect to a subgroup 23 5.4. An algorithm for solving the Conjugacy Pr...

* 0-7803-7952-7/03/$17.00 © 2003 IEEE. Abstract This paper presents a neural solution for clustering without pre-specifying the number of clusters. The presented clustering approach incorporates a harmonic neural network (HNN) and a codewordagglomerating neural network (ANN). The HNN harmonizes criteria of mean squared error and information entropy to exploit the substructure in the input data ...

is called an ascending HNN extension of G (or the mapping torus of the endomorphism φ). In particular, the ascending HNN extensions of free groups of finite rank are simply the groups given by presentations 〈x1, ..., xn, t | txit−1 = wi, i = 1, ..., n〉, where w1, ..., wn are words generating a free subgroup of rank n. In [BS], Borisov and Sapir proved that all ascending HNN extensions of linear...

Here we present a novel suite of projected 4D triple-resonance NMR experiments for efficient sequential assignment of polypeptide backbone chemical shifts in 13C/15N doubly labeled proteins. In the 3D HNN[CAHA] and 3D HNN(CO)[CAHA] experiments. the 13C(alpha) and lHalpha chemical shifts evolve in a common dimension and are simultaneously detected in quadrature. These experiments are particularl...

This paper proposes HNN, a holistic neural network structure for click-through rate (CTR) prediction in recommender systems. Empirically, equipped with HNN, the performance of deep neural networks for CTR prediction are improved on Criteo and Huawei App Store datasets.