iPhone 4 bom 成本明细

iPhone 4 teardown costs:

a simple table of the cost percentage:

lcd	28.5	15.16%
tyroscope	2.6	1.38%
proc	10.75	5.72%
dram	13.8	7.34%
nand	27	14.36%
power	4	2.13%
sensor	10	5.32%
touch scr	10	5.32%
camera	9.75	5.19%
battery	5.8	3.09%
mechanical	10.8	5.74%
elec-mech	14.4	7.66%
misc	5.5	2.93%
n/a	35.35	18.80%
total	188.25	100.13%
other details:
baseband	11.72	6.23%
wifi	7.8	4.15%

nc vs questa

category	feature	vlog/vsim	irun	description	same?
general		N/A	all ncverilog plus options can be used Options in LC can also be in UC.		diff
		-help	-h, -helpall	help	diff
		-version	-version	version	same
		N/A	-64bit	64bit	diff
		N/A	-clean	Deletes previous INCA_libs directory if it exists	diff
		N/A	-unbuffered	Do not buffer output	diff
compilation		N/A	-c	Parse and elaborate, do NOT simulate	diff
		N/A	-forceelab	Force ncelab to execute	diff
		N/A	-cdslib/hdlvar <arg>	Specify a cds.lib/hdl.var file to be used	diff
	access	+acc	-access rwc		diff
		-i/-gui	-gui	force interactive / Invoke the Graphical User Interface	diff
		-c	N/A	Command line mode	diff
		+incdir+<dir>	-incdir <dirs>	Specify directories to search for `include files	diff
		+libcell	-libcell	Define library modules (found with -v|-y search) as cells	diff
		natively supported???	-ovm	Turn on support for the OVM library	diff
	filelist	-f <filename>	-f <filename>	Scan file for args relative to irun invocation	same
		-L<lib dir>	-L<lib dir>	Directory to search for lib files	same
		-v <file>	-v <file>	Specify a library file to be used	same
		-y <directory>	-y <directory>	Specify a library directory to be used	same
		-work <library>	-work <library>	Library for command line	same
	coverage	N/A	-covdut	Select DUT for Coverage	diff
		N/A	-covoverwrite	Enable overwrite of coverage output files	diff
		N/A	-covworkdir <string>	Select coverage workdir	diff
		N/A	-coverage <string>	Enable coverage instrumentation	diff
		N/A	-covfile <file>	Specify coverage instrumentation control file	diff
		-coveropt	N/A	Specify a digit for code coverage optimization level: 1 through 4.	diff
		+cover[=sbceftx]	N/A	Enable code coverage metrics by specifying the characters	diff
	optimization	N/A	-debug	Equivalent to -access +rw, Specman debug	diff
		+acc=l	-linedebug	line debug	diff
	parameter	N/A	-defparam <arg>	Redefine the value of a Verilog parameter	diff
	macro/define	+define+<macro_name>[=<macro_text>]	+define+<macro_name>[=<macro_text>]	Define a macro from command line	same
		N/A	-ncvlogargs <string>	Pass arguments to Verilog parser	diff
		N/A	-ncelabargs <string>	Pass arguments to elaborator	diff
		-R [<simargs>]	-ncsimargs <string>	Pass arguments to simulator	diff
simulation		-timescale <arg>	-timescale <arg>	Set default timescale on Verilog modules	same
		-l <filename>	-l <filename>	Set logfile name	same
		N/A	-R	Simulate using last snapshot generated	diff
		-pli "<object list>"	-loadvpi/loadpli1 <arg>	Specify the PLI library_name:boot_routine(s)	diff
		-sv_seed <seed>	-svseed <seed>	Set SystemVerilog default RNG seed	diff
		-do <file>	-input <file>	Read TCL commands from file	diff

run level coding (codec)

Scan
After quantization, the DCT coefficients for a block are reordered to group together nonzero coefficients, enabling efficient representation of the remaining zero-valued quantized coefficients. The optimum reordering path (scan order) depends on the distribution of nonzero DCT coefficients. For a typical frame block a suitable scan order is a zigzag starting from the DC (top-left) coefficient.  Nonzero coefficients tend to be grouped together at the start of the reordered array, followed by long sequences of zeros.

The zigzag scan may not be ideal for a field block because of the skewed coefficient distribution and a modified scan order
"

Run-Level Encoding
The output of the reordering process is an array that typically contains one or more clusters of nonzero coefficients near the start, followed by strings of zero coefficients. The large number of zero values may be encoded to represent them more compactly, for example by representing the array as a series of (run, level) pairs where run indicates the number of zeros preceding a nonzero coefficient and level indicates the magnitude of the nonzero coefficient.

Higher-frequency DCT coefficients are very often quantized to zero and so a reordered block will usually end in a run of zeros. A special case is required to indicate the fin nonzero coefficient in a block.
Example:
Input array:        16,0,0, -3,5,6,0,0,0,0, -7, . . .
Output values:    (0,16),(2, -3),(0,5),(0,6),(4, -7). . .

In so-called "Two-dimensional" run-level encoding is used, each run-level pair is encoded as above and a separate code symbol, "last", indicates the end of the nonzero values.

If "Three-dimensional" run-level encoding is used, each symbol encodes three quantities, run, level and last. In the example above, if -7 is the fin nonzero coefficient, the 3D values are:
(0, 16, 0), (2, -3, 0), (0, 5, 0), (0, 6, 0), (4, -7, 1)
The 1 in the fin code indicates that this is the last nonzero coefficient in the block.

Quantization (codec)

A quantiser maps a signal with a range of values X to a quantised signal with a reduced range of values Y. It should be possible to represent the quantised signal with fewer bits than the original since the range of possible values is smaller.

A scalar quantiser maps one sample of the input signal to one quantised output value and a vector quantiser maps a group of input samples (a "vector") to a group of quantised values.

A simple example of scalar quantisation is the process of rounding a fractional number to the nearest integer, i.e. the mapping is from R to Z. The process is lossy (not reversible)

2 types of quantisers are listed here: a linear quantiser (with a linear mapping between input and output values) and a nonlinear quantiser that has a "dead zone" about zero (in which small-valued inputs are mapped to zero).


In image and video compression CODECs, the quantisation operation is usually made up of two parts: a forward quantiser FQ in the encoder and an "inverse quantiser" or (IQ) in the decoder.

A critical parameter is the step size QP between successive re-scaled values. If the step size is large, the range of quantised values is small and can therefore be ef?ciently represented (highly compressed) during transmission, but the re-scaled values are a crude approximation to the original signal.

 The forward quantiser in an image or video encoder is designed to map insignificant coefficient values to zero whilst retaining a reduced number of significant, nonzero coefficients.


Vector Quantisation
A vector quantiser maps a set of input data (such as a block of image samples) to a single value (codeword) and, at the decoder, each codeword maps to an approximation to the original set of input data (a "vector").

A typical application of vector quantisation to image compression [5] is as follows:
1.  Partition the original image into regions (e.g. M × N pixel blocks).
2.  Choose a vector from the codebook that matches the current region as closely as possible.
3.  Transmit an index that identi?es the chosen vector to the decoder.
4.  At the decoder, reconstruct an approximate copy of the region using the selected vector.

Transform coding (codec)

Transform coding is at the heart of the majority of video coding systems and standards.
Spatial image data (image samples or motion-compensated residual samples) are transformed into a different representation, the transform domain.

The two most widely used image compression transforms are the discrete cosine transform (DCT) and the discrete wavelet transform (DWT). The DCT is usually applied to small, regular blocks of image samples (e.g. 8 x 8 squares) and the DWT is usually applied to larger image sections ("tiles") or to complete images

• DCT

The DCT has proved particularly durable and is at the core of most of the current generation of image and video coding standards, including JPEG, H.261, H.263, H.263+, MPEG-l, MPEG-2 and MPEG-4. The DWT is gaining popularity because it can outperform the DCT for still image coding and so it is used in the new JPEG image coding standard (JPEG-2000) and for still "texture" coding in MPEG-4.

DCT become the most popular transform for image and video coding. There are two main reasons for its popularity: first, it is effective at transforming image data into a form that is easy to compress and second, it can be efficiently implemented in software and hardware.

The forward DCT (FDCT) of an N × N sample block isgiven by:
     Y = AXA(T)
and the inverse DCT (IDCT) by:
     X = A(T)YA

The transform matrix A for a 4 × 4 DCT is:
A =

0.5         0.5 0.5 0.5
0.653     0.271       0.271 −0.653
0.5 −0.5 −0.5         0.5
0.271 −0.653 −0.653     0.271

The forward DCT (FDCT) transforms a set of image samples (the "spatial domain") into a set of transform coefficients (the "transform domain"). The transform is reversible: the inverse DCT (IDCT) transforms a set of coefficients into a set of image samples.

The DCT has two useful properties for image and video compression, energy compaction (concentrating the image energy into a small number of coefficients) and decorrelution (minimising the interdependencies between coefficients).

A reasonable approximation to the original image block can be reconstructed from just these most significant coefficients.

 The DCT becomes increasingly complex to calculate for larger block sizes.

• DWT

 a wavelet transform is typically applied to a complete image or a large rectangular region ("tile") of the imag.


A single-stage wavelet transformation consists of a filtering operation that decomposes an image into four frequency bands. m. The top-left comer of the transformed image ("LC) is the original image, low-pass filtered and subsampled in the horizontal and vertical dimensions. The top-right comer ("W) consists of residual vertical frequencies .
 The bottom-left comer "LH" contains residual horizontal frequencies.
 The bottom-right comer "HH" contains residual diagonal frequencies.

This decomposition process may be repeated for the "LL" component to produce another set of four components: a new "LL" component that is a further subsampled version of the original image, plus three more residual frequency component.

The wavelet decomposition has some important properties. First, the number of wavelet "coefficients" (the spatial values that make up Figure 7.8) is the same as the number of pixels in the original image and so the transform is not inherently adding or removing information.
Second, many of the coefficients of the high-frequency components ("HH", "HL" and "LH" at each stage) are zero or insignificant. This reflects the fact that much of the important information in an image is low-frequency. Third, the decomposition is not restricted by block boundaries (unlike the DCT) and hence may be a more flexible way of decorrelating the image data (i.e. concentrating the significant components into a few coefficients) than the block-based DCT.

Wavelet-based compression performs well for still images (particularly in comparison with DCT-based compression) and can be implemented reasonably efficiently.

中国高速铁路

CRH：中国高速铁路，英文全称（CHINA RAILWAY HIGH-SPEED）目前已知有CRH1，CRH2，CRH3，CRH5。据称，由于中国人忌讳“4”谐音“死”故没有CRH4的型号。


CRH2和CRH5具备提速至300KM/H的条件。

CRH1庞巴迪-四方-鲍尔（BSP）生产，原型是庞巴迪为瑞典AB提供的Regina。200公里级别（营运速度200KM/h，最高速度250KM/h）。
编组型式：8辆编组，可两编组连挂运行动力配置：2（2M+1T）+（1M+1T）车种：一等车、二等车、酒吧坐车合造车定员（人）：670

客室布置：一等车2+2、二等车2+3

最高运营速度（km/h）：200
中间车辆长度（mm）：26600

车辆宽度（mm）：3328

车辆高度（mm）：4040
牵引电动机：265kW
CRH1共有三个派生车型，它们分别是CRH1A、CRH1B和CRH1E。

CRH2
南车四方（联合日本川崎）生产。
是以日本新干线的E2-1000型电动车组为基础，是继台湾高铁的700T型电联车后，第二款出口国外的新干线列车。供中国使用的CRH2型虽使用与E2-1000相同的电动机，由于其编组方式是4节动车配4节拖车，动力比日本的6M2T编组E2系小，因此在营运速度方面会比日本本土的E2系有所下调，最高营运时速为200公里。
CRH2系列有4个派生车型，它们分别是CRH2A、CRH2B、CRH2C和CRH2E。
编组型式：8辆编组，可两编组连挂运行（重联运行）
CRH2型电动车组，全部为8节或16节编组，动力分配形式各不相同；2A为4M+4T，2B为8M+8T，2C为6M+2T，2E为8M+8T。


车种：一等座车、二等座车、二等座车餐车。

车辆宽度（mm）：3380

车辆高度（mm）：3700

CRH3
北车唐山机车厂（联合西门子）生产，原型ICE3。编组形式为，8M0T。轴功率550kW，全车共16根动轴，平均分布于8辆车上，每车两台转向架，每台转向架均有一根动轴。
动力配置：全部为8节或16节编组，动力分配形式各不相同；3A/3C为4M+4T，3D目前暂不清楚。

车种：一等座车、二等座车、二等座车餐车

定员：601人
车辆宽度（mm）：3265

车辆高度（mm）：3890

CRH5
 北车长春客车厂（联合阿尔斯通）生产，原型阿尔斯通为芬兰国铁提供的SM3型。200公里级别（营运速度200KM/h，最高速度250KM/h）。
在CRH5中，CRH5-001A为原装进口车，CRH5-004A为散件组装车，CRH5-010A/011A/012A为采用部分进口部件的国产车。

编组型式：全部为8辆编组，可两编组连挂运行动力配置：（3M+1T）+（2M+2T）车种：一等车、二等车、酒吧坐车合造车定员（人）：602+2（残疾人）客室布置：一等车2+2、二等车2+3

最高运营速度（km/h）：200（具备提速到300km/h的条件）最高试验速度（km/h）：250
车辆宽度（mm）：3200
车辆高度（mm）：4270


中国高铁建设规划
四纵：
北京－上海：全长1318公里，纵贯京津沪和冀鲁皖苏四省，连接环渤海 和长江三角洲两大经济区 。
北京－武汉－广州－深圳：全长约2260公里，连接华北和华南地区。武 汉至广州段全长995公里，2005年6月开工 。
北京－沈阳－哈尔滨（大连）：全长约1700公里，连接东北和关内地区 。秦皇岛至沈阳段400 公里已于2003年建成 。
杭州－宁波－福州－深圳：全长约1600公里，连接长江、珠江三角洲 和东南沿海地区。

四横：
徐州－郑州－兰州：全长约1400公里，连接西北和华东地 区。已开工建设郑州至西安段455公里 。
杭州－南昌－长沙：全长约880公里，连接华中和华东地 区 。
青岛－石家庄－太原：全长约770公里，连接华北和华东 地区。已开工建设建设石家庄至太原段205公里。
宁汉蓉（南京－武汉－重庆－成都）：全长约1600公里， 连接西南和华东地区。已开工建设南京至合肥段、武汉至 合肥段、宜万段、成遂渝段

地铁系统

地铁和轻轨
为了增强轨道的稳定性，减少养护和维修的工作量，增大回流断面和减少杂散电流，地铁和轻轨都选用轨距为1435毫米的国际标准双轨作为列车轨道，与国铁列车选用的轨道规格相同，并没有所谓的钢轨重量轻重之分。
划分两者区别的依据是所选用列车的规格。按照国际标准，城市轨道交通列车可分为A、B、C三种型号，分别对应3米、2.8米、2.6米的列车宽度。凡是选用A型或B型列车的轨道交通线路称为地铁，采用5～8节编组列车；选用C型列车的轨道交通线路称为轻轨（上海轨道交通8号线除外），采用2～4节编组列车，列车的车型和编组决定了车轴重量和站台长度。在我国的规范中是指，轴重相对较轻，单方向输送能力在1万～3万人次的轨道交通系统，称为轻轨；每小时客运量3万～8万人次的轨道交通系统，称为地铁。

通常一个轨道交通网络，由三个等级的线网有机组合而成：区域快线系统（R线）、城区干线系统（M线）和辅助联络系统（L线）。区域快线系统，类似于美国的通勤铁路和日本的JR通勤铁路，起终点通常在郊县，有的经过主城区，有的不经过主城区。城区干线系统，则是主要为主城区交通服务的，起终点通常在城市建成区的边缘或城市外围城镇组团中。辅助联络系统，顾名思义，就是在整个线网中起到辅助和沟通作用的线路，他们通常采用比M线稍低一些的制式，运能相对也较小。
R线追求的是高速，因此站间距大，对列车速度的要求高，通常采用电力机车，而M线追求的是便捷，因此站间距比较小，对列车运行速度的要求不高，通常采用城轨车辆。
容量（车型）
地铁通常采用A型车和B型车，这两种车的区别在于几何尺寸和载客量。A型车通常长22米，宽3米（当然也有南京地铁使用的3.2米宽体A车），B型车通常长19米，宽2.8米，因此同样节数的一列列车，使用A车的载客量要大于B车。例如，6节编组A车的额定载客量可以达到1830人，而B车就只有1440人。
编组
以无锡轨道交通1号线为例。客流预测远期高峰小时单向客流量为31300人次，也就是说高峰小时在同一方向上，最大通过的客流量有31300人次之多。地铁设计规范规定，新建地铁的服务水平不得低于每小时开行30对的指标，也就是说，每个小时在同一方向上至少要发30班列车。一列4B，5B，6B列车的载客量分别为950人、1195人、1440人。用31300分别除以这三个数字，得到32.94、26.19和21.73。可以看出，如果采用4B编组，则必须每小时开行33对才能达到客流需要，也就是说系统长期将处在高强度满负荷状态，这显然是极其不利于安全的，因此4节B车编组无法满足无锡1号线的需要。而如果采用6B编组，则每小时只需要开行22对，相比较起来，发车间隔要比采用5B编组来的大，这也有些不利于提高服务水平。所以，初步看来选取5B是合适的。进一步验算，采用5B编组，假设每小时开行30对，则一小时单向可以输送35850人次，将它除以31300，得到1.145，意味着运能储备达到14.5%。
轨道交通列车通常只采用偶数节编组，比如2节，4节，6节，8节，很少有采用奇数节的（请注意是很少有，而不是没有，例如高雄地铁初期采用3节A车编组）。
众所周知，地铁列车分为动车和拖车，一节带受电弓或者受流器的动车和一节带空气压缩机的动车为一个单元，再加上一头一尾两节拖车，这就是为什么绝大多数城市的快轨列车编组都是偶数节的道理。我国通常用A代表拖车，用B代表带受电弓或授流器的动车，用C代表只带空气压缩机的动车。因此上海地铁1号线的6编，就是4动2拖A-B-C-B-C-A，8编就是6动2拖A-B-C-B-C-B-C-A。偶数节的好处，简直不言而喻。例如调配组合方便，购车方便，动力均衡，不同线路的车辆互换性好，可以增加系统运营的稳定性和可靠性，降低成本等等。
奇数节就不同的，如果是5编，按照无锡这次上报的方案，就是3动2拖A-B-C-B-A。这将会带来几个比较显著的问题：首先，动车不成单元，先是给购车带来了不便，带受电弓的动车数是带空气压缩机的动车数的一倍，无形中又增加了以后调配的难度和维护的成本。其次，动力不均衡，牵引和辅助系统的配备有区别。采用偶数节编组，例如6节，只需要配置2个辅助系统，而采用5节可能就要配置更多的辅助系统，无论是造价还是运营成本都显然是后者大于前者。可能这也就是为什么鲜有城市采用奇数节编组的道理。
动力
电气化铁路常用的两种供电网络方式包括接触网供电和第三轨供电。第三轨供电的概念就是在列车行走的两条路轨以外，再加上带电的钢轨。这条带电钢轨通常设于两轨之间或其中一轨的外侧。电动列车的集电装置在带电路轨上接触并滑行，把电力传到列车上。这种集电装置在英语称为 shoe，中译为集电靴（取流靴）。第三轨安装在轨道梁上，电动车辆取流靴与第三轨接触面大且对其磨损极小。采用第三轨式接触网的优点是工程易于安装，检修方便、维护简单，寿命长。从技术角度来讲,由于集电靴在高速之下难以准确地抓紧带电轨，故采用第三轨供电的线路速度不能太高。理论上来讲，采用轨道供电系统的列车的时速上限是 160 公里。另外，第三轨有触电的风险，只能用于封闭线路，因此不适用于以地面线路为主的铁路运输系统中。另一方面，地面重型铁路系统为了高速客运和货运重载的需要，会使用更高的电压，如25千伏的供电系统，这也是第三轨系统所不能承受的。

在铁路和城市轨道交通系统中，架空接触网只有导线的一个电极，电力机车通过集电弓取电，再通过金属轮轨回流到电网中。在无轨电车等使用胶轮的系统中，架空接触网有两根互不接触的两根接触导线（简称触线），通过两个集电杆取电。架空接触网的悬挂类型大致为三种：简单悬挂，链式悬挂，刚性悬挂。刚性悬挂是以硬质的金属条（通常是铜条）代替软质的导线的新型悬挂方式。刚性悬挂使用集电弓，没有使用集电靴的第三轨容易脱落的缺点，可以达到更高的运行速度。