BOOL CALLBACK Pic_OnDraw(HELE hEle,HDRAW hDraw)
{
RECT rect;
XEle_GetClientRect(hEle,&rect);
if(PICTURE(hEle)->hImage_bk)
{
XDraw_HImageSuper_(hDraw,PICTURE(hEle)->hImage_bk,&rect);
}
if(((ele_*)hEle)->bBorder)
{
HBRUSH hBrush=XDraw_CreateSolidBrush_(hDraw,((ele_*)hEle)->borderColor);
XDraw_FrameRect_(hDraw,&rect,hBrush);
//DeleteObject(hBrush);
}
return TRUE;
}
/// @brief 设置图片.
/// @param hEle 元素句柄.
/// @param hImage 图片句柄.
void WINAPI XPic_SetImage(HELE hEle,HIMAGE hImage)
{
IsPictureDebug(hEle,__FUNCTION__);
if(hImage)
{
IsHImageDebug(hImage,__FUNCTION__);
}
Image_AddImage(PICTURE(hEle)->hImage_bk,hImage);
}
void CALLBACK Pic_OnDestroy(HELE hEle) //销毁
{
if(PICTURE(hEle)->hImage_bk) XImage_Destroy(PICTURE(hEle)->hImage_bk);
}
NORMAL (L"@@Feedforward neural networks 4. Command overview|4. Command overview@") MAN_END MAN_BEGIN (L"Feedforward neural networks 1. What is a feedforward neural network?", L"djmw", 20040426) INTRO (L"A feedforward neural network is a biologically inspired classification algorithm. " "It consist of a (possibly large) number of simple neuron-like processing %units, organized in %layers. " "Every unit in a layer is connected with all the units in the previous layer. " "These connections are not all equal, each connection may have a different strength or %weight. " "The weights on these connections encode the knowledge of a network. " "Often the units in a neural network are also called %nodes.") NORMAL (L"Data enters at the inputs and passes through the network, layer by layer, until it arrives at the outputs. " "During normal operation, that is when it acts as a classifier, there is no feedback between layers. " "This is why they are called %%feedforward% neural networks. ") NORMAL (L"In the following figure we see an example of a 2-layered network with, from top to bottom: " "an output layer with 5 units, a %hidden layer with 4 units, respectively. The network has 3 input units.") PICTURE (5, 5, drawFFNet_345) NORMAL (L"The 3 inputs are shown as circles and these do not belong to any layer of the network (although the inputs " "sometimes are considered as a virtual layer with layer number 0). Any layer that is not an output layer is a " "%hidden layer. This network therefore has 1 hidden layer and 1 output layer. The figure also shows all the " "connections between the units in different layers. A layer only connects to the previous layer. ") NORMAL (L"The operation of this network can be divided into two phases:") NORMAL (L"@@Feedforward neural networks 1.1. The learning phase|1. The learning phase") NORMAL (L"@@Feedforward neural networks 1.2. The classification phase|2. The classification phase") MAN_END MAN_BEGIN (L"Feedforward neural networks 1.1. The learning phase", L"djmw", 20040428) INTRO (L"During the learning phase the weights in the FFNet will be modified. " "All weights are modified in such a way that when a pattern is presented, " "the output unit with the correct category, hopefully, will have the largest output value.") ENTRY (L"How does learning take place?") NORMAL (L"The FFNet uses a %supervised learning algorithm: besides the input pattern, "
"@PitchTier, @DurationTier, @Harmonicity, @PointProcess.") NORMAL (L"In Praat, these functions have a contiguous ##time domain#, i.e. " "a single time stretch with a @@start time@ and an @@end time@. " "The @@total duration@ of such a function is the difference between the start time " "and the end time. There are up to five ways to see the time domain " "of an object.") ENTRY (L"The time domain in editor windows") NORMAL (L"If you select an object that is a function of time and click ##View & Edit#, an editor window " "will appear on the screen. The rectangle at the bottom will show the start time, " "the end time, and the total duration.") ENTRY (L"The time domain in the picture window") NORMAL (L"If you select an object that is a function of time and choose one of the #Draw commands, " "the window that pops up will invite you to supply a time range. If you keep this time range " "at its standard setting (from 0.0 to 0.0 seconds), Praat will draw the object for the whole time domain " "and print the start time and the end time below the horizontal axis (if #Garnish is on):") PICTURE (5, 2.5, draw_TimeDomain_Sound) PICTURE (5, 2.5, draw_TimeDomain_Pitch) ENTRY (L"The time domain in the Info window") NORMAL (L"If you select an object that is a function of time and click #Info, " "the Info window will tell you the start time, the end time, and the total duration (among other properties of the object).") ENTRY (L"Time domain query commands") NORMAL (L"If you select an object that is a function of time, " "the following three commands will become available in the #Query menu:") LIST_ITEM (L"##Get start time") LIST_ITEM (L"##Get end time") LIST_ITEM (L"##Get total duration") NORMAL (L"If you choose one of these commands, the Info window will tell you the result, " "expressed in seconds. These commands are most useful in a Praat script. Example:") CODE (L"selectObject: \"Pitch hello\"") CODE (L"startTime = Get start time") CODE (L"endTime = Get end time")