ARP test mode. According to the idea we design the arithmetic for the key part, first the system sends a message to the target machine, and then system wait for the response. Once system receives a message, it starts to analyze the message, according to the message s parameter system judges whether the message satisfies the conditions. Once the message satisfies all the conditions, the system thinks the machine is sniffing, and adds this machine into the list of sniffing machines. On this basis the detection has done well, and at the same time we insert the result into the log database for inquire and analyze later.
超寬帶UWB,包括:uwb.mdl: UWB model - open this to begin.
uwb_lib.mdl: Library blocks for UWB model.
uwb_init.m: Initialization called before model is loaded.
uwb_settings: Sets up structure containing system parameters ( uwb in workspace).
uwb_imr.m: Initializes UWB channel impulse response.
uwb_sv_*.m: Four M-files used to generate channel impulse responses (MAT files).
The BNL toolbox is a set of Matlab functions for defining and estimating the
parameters of a Bayesian network for discrete variables in which the conditional
probability tables are specified by logistic regression models. Logistic regression can be
used to incorporate restrictions on the conditional probabilities and to account for the
effect of covariates. Nominal variables are modeled with multinomial logistic regression,
whereas the category probabilities of ordered variables are modeled through a cumulative
or adjacent-categories response function. Variables can be observed, partially observed,
or hidden.
The Window Design Method
The basic idea behind the design of linear-phase FIR filters using the window
method is to choose a proper ideal frequency-selective filter [which always has
a noncausal, infinite duration impulse response] and then truncate its impulse
response hd[n] to obtain a linear-phase and causal FIR filter h[n]. To truncate the
impulse response of the ideal filter a time window w[n] is used. Available windows
in Matlab are rectangular [or boxcar in Matlab], bartlett, hamming, hanning
The Hilbert Transform is an important component in communication systems, e.g. for single sideband modulation/demodulation, amplitude and phase detection, etc. It can be formulated as filtering operation which makes it possible to approximate the Hilbert Transform with a digital filter. Due to the non-causal and infinite impulse response of that filter, it is not that easy to get a good approximation with low hardware resource usage. Therefore, different filters with different complexities have been implemented.
The detailed discussion can be found in "Digital Hilbert Transformers or FPGA-based Phase-Locked Loops" (http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4629940).
The design is fully pipelined for maximum throughput.
This application note considers the design of frequency-
selective filters, which modify the frequency content
and phase of input signals according to some specification.
Two classes of frequency-selective digital filters
are considered: infinite impulse response (IIR) and finite
impulse response (FIR) filters. The design process
consists of determining the coefficients of the IIR or FIR
filters, which results in the desired magnitude and
phase response being closely approximated.
This application note considers the design of frequency-
selective filters, which modify the frequency content
and phase of input signals according to some specification.
Two classes of frequency-selective digital filters
are considered: infinite impulse response (IIR) and finite
impulse response (FIR) filters. The design process
consists of determining the coefficients of the IIR or FIR
filters, which results in the desired magnitude and
phase response being closely approximated.
This software is developed to provide ease with controller design. For PID control, options are given
to design and analyse the compensated and uncompensated system. You are free to choice among Proportional
PI, PD and PID mode of control. Both frequency and time domain characteristics can be observed. Special
Menus are given to observe time and frequency response plots. For Statefeedback controller similar options
are given. But this is limited to second order system only.
