In spite of its problems with interactions, the first-quantized Klein-Gordon equation is a satisfactory theory free spinless particles. Moreover, usual may be extended to describe Lorentz-violating behavior, same types that exist can in second-quantized scalar field theories. However, because construction requires restriction positive-energy modes, Hilbert space inner product and position opera...

We propose BinaryRelax, a simple two-phase algorithm, for training deep neural networks with quantized weights. The set constraint that characterizes the quantization of weights is not imposed until the late stage of training, and a sequence of pseudo quantized weights is maintained. Specifically, we relax the hard constraint into a continuous regularizer via Moreau envelope, which turns out to...

This work explores the edge agreement problem of second-order nonlinear multiagent system under quantized measurements. Under the edge agreement framework, we introduce an important concept about the essential edge Laplacian and also obtain a reduced model of the edge agreement dynamics based on the spanning tree subgraph. The quantized edge agreement problem of second-order nonlinear multi-age...

This work explores the edge agreement problem of second-order nonlinear multiagent system under quantized measurements. Under the edge agreement framework, we introduce an important concept about the essential edge Laplacian and also obtain a reduced model of the edge agreement dynamics based on the spanning tree subgraph. The quantized edge agreement problem of second-order nonlinear multi-age...

This work explores the edge agreement problem of second-order multi-agent system with dynamic quantization under directed communication. To begin with, by virtue of the directed edge laplacian, we derive a model reduction representation of the closed-loop multi-agent system depended on the spanning tree subgraph. Considering the limitations of the finite bandwidth channels, the quantization eff...

This paper studies the problem of quantized feedback control for sampled-data systems which employ a quantizer to transmit feedback signals at a given sampling rate. The so-called static (memoryless) quantizers are considered. Given a continuous-time system, the design objective is to stabilize the system or to achieve certain performance using the coarsest quantization density. We study the po...

In this paper we propose a quantized time series algorithm for spoken word recognition. In particular, we apply the algorithm to the task of spoken Arabic digit recognition. The quantized time series algorithm falls into the category of template matching approach, but with two important extensions. The first is that instead of selecting some typical templates from a set of training data, all th...