Cells of Escherichia coli B infected with the immunity-negative (imm2) mutant of bacteriophage T4 are able to develop a substantial level of immunity to superinfecting phage ghosts if the ghost challenge is made late in infection. This background immunity is not seen in infections with phage carrying the spackle (s) mutation in addition to the imm2 lesion. The level of immunity in s(-) infectio...

Ground maneuvering target tracking is a class of nonlinear and/or no-Gaussian filtering problem. A new interacting multiple model unscented particle filter (IMMUPF) is presented to deal with the problem. A bank of unscented particle filters is used in the interacting multiple model (IMM) framework for updating the state of moving target. To validate the algorithm, two groups of multiple model f...

In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm processes all the models through a Markov Chain to simultaneously enhance the model...

The problem of tracking a tactical ballistic missile is complicated by the varying target dynamics in the boost, exo-atmospheric and endo-atmospheric phases of flight. A single Kalman filter tuned for constant velocity or constant acceleration is not based upon the correct underlying physical model of these dynamics. By including models with all of the correct dynamics, an Interacting Multiple ...

Abstract – Classical vehicle tracking approaches for highway scenarios use a Kalman–filter with a single dynamic model optimised to a single driving manoeuvre. In contrast, the Interacting Multiple Model (IMM) filter allows for several parallel models which are combined to a weighted estimate. Choosing models for different driving modes such as constant speed, acceleration and strong accelerati...

Catastrophic forgetting is a problem of neural networks that loses the information of the first task after training the second task. Here, we propose a method, i.e. incremental moment matching (IMM), to resolve this problem. IMM incrementally matches the moment of the posterior distribution of the neural network which is trained on the first and the second task, respectively. To make the search...

Development of the sporophyte and gametophyte generations of the brown alga E. siliculosus involves two different patterns of early development, which begin with either a symmetric or an asymmetric division of the initial cell, respectively. A mutant, immediate upright (imm), was isolated that exhibited several characteristics typical of the gametophyte during the early development of the sporo...

In this paper, we present an interesting filtering algorithm to perform accurate estimation in jump Markov nonlinear systems, in case of multi-target tracking. With this paper, we aim to contribute in solving the problem of modelbased body motion estimation by using data coming from visual sensors. The Interacting Multiple Model (IMM) algorithm is specially designed to track accurately targets ...

G. Impellizzeri, S. Boninelli, F. Priolo, E. Napolitani, C. Spinella, A. Chroneos, and H. Bracht MATIS IMM-CNR and Dipartimento di Fisica e Astronomia, Università di Catania, Via S. Sofia 64, 95123 Catania, Italy MATIS IMM-CNR and Dipartimento di Fisica, Università di Padova, Via Marzolo 8, 35131 Padova, Italy IMM-CNR, VIII Strada 5, 95121 Catania, Italy Department of Materials Science and Meta...