Tham khảo tài liệu 'discrete time systems part 15', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Discrete-Time Dynamic Image-Segmentation System 409 The g - was already defined in Eq. 2 . The third term on the right hand side of Eq. 3a denotes the th neuron s self-feedback and external inputs from neighboring neurons in which Lị represents an index set for neurons connected to the th one. Therefore the maximum number of elements in Lị is five in the architecture in Fig. 2 a . The Mị expresses the number of elements in Lị. Note that when the th neuron has no connection to neighboring neurons including itself . Mị 0 we treat it as wx Mị 0 because division by zero occurs. As seen in Eq. 3c the dynamics of a global inhibitor is improved from that in Eq. 1c so that it can detect one or more firing neurons moreover it suppresses the activity levels of all neurons via negative couplings described at the fourth term in the right hand side of Eq. 3a . Therefore when we set all the parameter values in Eq. 3 to those described in Sec. only neurons with self-feedback can generate oscillatory responses. Scheme of dynamic image segmentation There is an image segmentation scheme using our neuronal network system in Fig. 3. For simplicity let us now consider a simple gray-level image with 3 X 3 pixels. The image contains two image regions consisting of the same gray-level pixels the first is composed of the first and fourth pixels and the second is made up of only the ninth pixel. Nine neurons are arranged in a 3 X 3 grid for the given image. The value of DC input dị is associated with the gray level of the ịth pixels. A neuron with a high DC-input value forms positive self-feedback and also connects to neighboring ones with similar DC-input values. Therefore the red and blue neurons in this schematic have positive self-feedback connections and can generate oscillatory responses the others corresponding to black pixels have no self-feedback and do not fire. Direct connection is formed between the red neurons because they correspond to pixels with the same gray .
