<span>This study aims to find the best artificial neural network weight values be applied autonomous vehicle system with ultrasonic multisensor. The implementation of in required long time process due its training process. Therefore, this research is using offline before implementing online by embedding obtain outputs faster according desired targets. Simulink were used train offline. Eig...

 Ambiguity in the inputs of the models is typical especially in portfolio selection problem where the true distribution of random variables is usually unknown. Here we use robust optimization approach to address the ambiguity in conditional-value-at-risk minimization model. We obtain explicit models of the robust conditional-value-at-risk minimization for polyhedral and correlated polyhedral am...

This paper proposes a non-iterative computational algorithm for the design of discrete-time fixed order controller for an H optimization problem. Using the coprime factors and pole placement constraints, the fix-order controller design is reformulated as a convex optimization problem. The solutions are obtained using linear matrix inequality techniques. An aircraft model with 3-inputs and 3-out...

Document embeddings serve to supply richer semantic content for downstream tasks which require fixed length inputs. We propose a novel unsupervised framework by which to train document vectors by using a modified Recurrent Neural Network Language Model, which we call DRNNLM, incorporating a document vector into the calculation of the hidden state and prediction at each time step. Our goal is to...

This paper asks what classes of input signals are sufficient in order to completely identify the input/output behavior of generic bilinear systems. The main results are that step inputs are not sufficient, nor are single pulses, but the family of all pulses (of a fixed amplitude but varying widths) do suffice for identification. Partially supported by NSF grants DMS-0504557 and DMS-0614371 Part...

We consider spiking neural P systems as devices which can be used to perform some basic arithmetic operations, namely addition, subtraction, comparison and multiplication by a fixed factor. The input to these systems are natural numbers expressed in binary form, encoded as appropriate sequences of spikes. A single system accepts as inputs numbers of any size. The present work may be considered ...

Predicting properties of molecules requires functions that take graphs as inputs. Molecular graphs are usually preprocessed using hash-based functions to produce fixed-size fingerprint vectors, which are used as features for making predictions. We introduce a convolutional neural network that operates directly on graphs, allowing end-to-end learning of the feature pipeline. This architecture ge...

In this paper, a state and unknown input observer is proposed for discrete-time linear systems with bounded unknown inputs and measurement disturbances. The design procedure is formulated using a set of linear matrix inequalities, and leverages delayed (or fixed-lag) estimates. The observer error states and/or user-defined performance outputs are guaranteed to operate at pre-specified performan...

 The un-augmented open loop 6-DOF Aerosonde exhibits poor stability and control characteristics in compliance with MIL-F8785C flying quality standards.  As in most classical fixed wing aircrafts, the control inputs to Aerosonde result in pitch, roll and yaw rate responses (rate command characteristics). This has made manual trimming of the UAV, at a given flight condition, with a human pilot-...