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2012年度試験問題解説
参考程度に
問3、問6は2013年度の解答参照
問10は今年度は試験の範囲外
問1
• フーリエ変換、離散フーリエの関係、ラプラス変換、z変換の関
係
フーリエ変換 離散フーリエ変換
z変換ラプラス変換
離散化(2013
年問1)
離散化
課題4 No.9 37枚目参照
問2
• 前半は2013年度課題6参照
後半
• 有限長インパルス応答システム(FIR)
• インパルス応答の長さが有限
• 𝑦 𝑛 = 𝑘=0
𝑀
𝑥 𝑛 − 𝑘 ℎ[𝑘]←有限長になっている
• 無限長インパルス応答システム(IIR)
• インパルス応答の長さが無限
• 通常の畳み込みの計算は無限の総和になるため計算できないが,再帰
的に計算すれば有限の総和で計算可能
• 𝑦 𝑛 = 𝑘=0
𝑀
𝑎 𝑘 𝑥 𝑛 − 𝑘 − 𝑘=0
𝑁
𝑏 𝑘 𝑦 𝑛 − 𝑘
• ↑過去の出力も利用して有限長に変形している
問4
• 畳み込みと相関関数(講義資料No.2、24-27枚目)
• 基本的に畳み込みと相関関数の差異は上記講義資料にある
解釈1と2のような考え方の違いと同様に考えればよい.(相関
関数は畳み込みの解釈2を,畳み込む関数を反転させないよ
うに定義しなおしたともいえる)
• 畳み込みはフィルタリング(画像の平滑化、ローパスフィルタ
など)、相関関数は音声認識、テンプレートマッチングに使わ
れる
問5
• フーリエ変換をして、振幅のピークを求めるという解答は0点
になるとのことなので、他のアプローチを考える
• 1、元の信号と特定の周波数を持った正弦波との類似度を求
め最も高い類似度を持った周波数を求める周波数とする
• 2、元の信号が周期的な正弦波であるならばゼロ交差点の情
報から周波数を求めるという方法でもよい
問7
• 窓関数(講義資料No.7)課題35などを参照
• 窓関数は短時間フーリエ変換を行う時に信号を切り出す必要
があるが,この時元の周波数特性をできるだけ変形させない
ように切り出したい
• 普通に矩形波で切り出した場合は周期関数化した時に不連
続となる部分が発生するのでそこで異なる周波数成分が発生
してしまう.そこで切り出す信号の端を0にするなどして滑らか
につなげることにより,切り出すことによる周波数成分の変形
を抑えている
問7
• 窓関数には様々な種類がありハミング窓やハニング窓、ブ
ラックマン窓などがある.これらの窓関数は扱う信号によって
適切なものを選ぶ必要がある.
• 信号の最小単位は時間窓を大きくとれば周波数スペクトルの
分解能が大きくなり、時間窓を小さくとれば周波数スペクトル
の分解能が大きくなるということに注意して,決めなければな
らない(講義中の窓関数の説明の時に見せたスペクトログラ
ムの拡大図参照) 信号の幅Δfと周波数スペクトルの分解能
の幅ΔFにはΔfΔF>=1/2という関係があるのでどちらの分解能
も高くすることは不可能である
問8
• 問2と同じように過去の出力も用いて表すことにより有限長の
フィルタに近似することができる…
問9
• 講義資料No.8 33枚目
• あらかじめコードブックを用意しておく
C1:(c11 c12 … c1k)
C2:(c21 c22 … c2k)
…
CN:(cN1 cN2 … cNk)
あるk個のサンプルを入力信号から切り出した時,この切り出し
た信号とコードブックを比較して最も似ている物を出力する
問9
• ここで各コードブックの選ばれる確率をあらかじめ知っている
ものとする.つまり
C1:(c11 c12 … c1k)…50%
C2:(c21 c22 … c2k) …10%
…
CN:(cN1 cN2 … cNk) …1%
• このとき,C1:1,C2:01,…,CN:0000…001のように符号化して
出力(情報理論の講義のハフマン符号化やランレングス符号
化など)することによりデータを圧縮させることができる

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ディジタル信号処理 試験解説 2012年実施分